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Is it common for an undergraduate thesis in pure mathematics to prove something new?

What do undergraduate students in mathematics do for their thesis, if they have done one, besides expository or applied math?

I was thinking that the kind of research they do is something applied, say using math in social sciences or a problem in one of the less rigorous natural sciences, or discussing such a problem (that's what expository is, right?).

To me it seems something non-expository or non-applied is an original contribution to mathematics, something that PhD students do.

I attended some pure math undergraduate thesis presentations. I was quite surprised: Did they prove anything new? Never bothered to ask due to fear of looking stupid. Would it be out of the ordinary to expect an undergraduate proves something new? If they did not prove anything new, what the heck are they talking about?

It seems like if it's not new, they are giving a lecture. If it's new, that seems like a PhD-level accomplishment.

I mean, do math undergraduates frequently prove new things?

  • mathematics
  • research-undergraduate

aparente001's user avatar

  • 6 "Anything new" is rather broad. I myself proved "something new" in by bachelors thesis, in the sense that nobody answered that particular question rigorously before. Was it deep? Probably not. Could I have published it? I don't think so. Still, it was new . –  Raphael Commented Jul 30, 2015 at 8:05
  • Depending on the country and the quality of the teaching, yes it is possible. If you have a Professor who gives you an actual problem knowing you have been taught the right modules/topics to investigate it, yes. If you have little teaching and then are told to pick a topic (as it happens in some places) then the chance is significantly lower. –  DetlevCM Commented Jul 30, 2015 at 12:03
  • 1 @DetlevCM I'm guessing there may be 1 for every dozens or hundreds. I was actually wondering about the average batch of undergrad math majors whose thesis is in pure math. My guess is in the first place not many math majors will do pure math in their thesis. So what about those who do? They actually try to prove something? What happens if they cannot prove that particular conjecture in a month after they come up with the proposal after a month? 2 months left in the semester. So what happens? –  BCLC Commented Jul 30, 2015 at 16:09
  • 1 @JackBauer Yes, that Enigma - I only covered the rotors and left out the switchboard but the switchboard is the trivial part. Heck, I suspect I could write an implementation fairly easily nowadays having gotten better at programming since. (Side note, its not cracking Enigma, its encoding and decoding which is really trivial.) –  DetlevCM Commented Jul 30, 2015 at 17:05
  • 1 @JackBauer Something like that. Some researchers claimed a property of the things they worked with; it was crucial for their method to work, but they did not provide a proof. (I don't know if they could have.) I filled that gap. My advisor found it, and I had the luck that it was a reasonably scoped task that took mostly undergrad stuff plus some tinkering. (I think he (and I) hoped I'd happen upon a case where they were wrong, but they weren't.) –  Raphael Commented Jul 30, 2015 at 21:28

5 Answers 5

I'm going to disagree with Oswald. In my experience, undergraduate students do not often prove new things in pure math. I wouldn't even say master's theses often contain new results. There are a few main reasons for this.

Firstly, pure mathematics operates at a level that is not very accessible for most undergraduates, even those doing research. Undergraduates doing research are often well out of their depth and holding on for dear life. This can mostly be attributed to just not having enough time to get up to speed with what is considered modern mathematics. Most courses in mathematics at the undergraduate level are about math from 50-100 years ago (if not older).

Secondly, undergraduates do not often have the mathematical experience to know what the right plan of attack is when faced with an abstract and new problem and they may not know how to check their work thoroughly to make sure there are no major oversights or blunders. A lot of mathematics involves lateral thinking and it takes a lot of time to build those connections. The hardest part of a pure math PhD (in my opinion) is learning how to attack a problem no one has considered before. Standard techniques that others used may not be useful at all to you for one reason or another. An undergraduate won't have the creativity to navigate this kind of issue because the kind of creativity that is needed comes with a lot of experience. Even when an undergraduate student thinks they've proved something, the nuances of their argument likely will not be apparent to them. (This is especially true when it comes to functional analytic/measure theoretic arguments - the devil is in the details.) Thus a proposed proof may not even be close to being right.

Lastly, not many undergraduates in pure math do research because the gap they have to overcome between coursework and modern mathematics is pretty substantial. Those that make contributions in pure math are those that are very, very talented and have very thorough backgrounds (backgrounds that rival master's/PhD students).

Undergraduates in pure math are not expected to make contributions. That is not what research is about for them. Introducing an undergraduate to research serves a couple of different purposes: it introduces them to more advanced topics and it gives them a taste of what research is like so that they can make an informed decision about whether or not graduate school is right for them. As such, the theses are more like surveys of a specialized topic in mathematics. There is a lot of independent learning involved and there may be some unique examples, insights, and connections contained therein. They may not be presenting "original" work, but poster sessions are there to present what they've learned regardless of whether or not it was original. So yes, it is kind of like a lecture. They are undergraduates and far from being experts in their field.

Note that I am not saying that no undergraduate ever produces new results in pure math (there are some high school students that are better than most PhDs), but it is not a common occurrence and is not expected or considered the norm.

Cameron Williams's user avatar

  • 27 Bingo. Exactly. Further, I think it is bad to promote the mythology that "undergrads can do meaningful research in mathematics" if only because it sets of unrealistic expectations, so that "everyone fails". That is, it does not help anyone to "assure" them that "they can do research while undergraduates", because most likely they will not, and this is not failure. And so on. For that matter, many graduate students misunderstand the degree of "originality/creativity" that will actually play a role in their thesis, since the bulk of the work is assimilation of known techniques... –  paul garrett Commented Jul 29, 2015 at 21:09
  • 8 I think a large part of the difference here is subfield. It is very rare for an undergraduate to make a substantial contribution anywhere, or any contribution to a subfield requiring a large amount of background. On the other hand, it's not so unusual for undergraduates to be able to prove new results in many areas of combinatorics, even if these results are unlikely to be interesting to anyone except other undergraduates working on follow-up projects. –  Alexander Woo Commented Jul 29, 2015 at 22:15
  • 2 I fully agree with @AlexanderWoo (and, perhaps counter-intuitively, Cameron's Answer): I think undergrads can definitely do bona fide research, in combinatorics if nowhere else. But, it is probably is likely that most undergrads don't do original research. –  pjs36 Commented Jul 29, 2015 at 22:24
  • 8 @Alexander Woo - I think it is important to distinguish between undergraduates working alone (who are indeed unlikely to produce much publishable work) versus undergraduates working in collaborations with faculty. For example, the well-known Duluth REU run by Gallian states they have over 200 published papers, in professional journals. These papers seem to be no more likely to be "uninteresting to anyone" than all the other papers in those journals :) See d.umn.edu/~jgallian/progbib.html –  Oswald Veblen Commented Jul 29, 2015 at 22:31
  • 3 @JackBauer - see the link that OswaldVeblen provided. All those papers were written by undergrads. Personally I coauthored an REU paper as an undergraduate, and my undergraduate thesis also had original results in graph theory, but I went into computer programming for a couple years and didn't publish before those results ended up (completely independently) as part of someone else's PhD dissertation. If you want details, e-mail me; I'm using my real name and can be easily found by Google. –  Alexander Woo Commented Jul 30, 2015 at 22:49

The answers so far contain a yes and a no, so let me add a yes-and-no.

Undergraduates can - and often do - prove new things, but hardly ever anything of importance. It is up to the advisor to find an interesting question which is simple enough to serve as the topic of a thesis, but not yet dealt with in the literature. Different from a Ph.D., a bachelor or master thesis is heavily constrained in time, so as an advisor you should only give a topic if you are pretty certain that something can be done by an unexperienced researcher in short time. On the other hand just repeating the literature is boring for the student. One way to find good topics is to look at what is often referred to as folklore: Every textbook contains the theorem that X implies Y, and every expert knows that quasi-X already suffices, but noone bothered to write it up. This will most probably not be worth a publication, but proving a theorem not yet contained in the literature is motivating. Another simple method is looking at all the things you excluded from your own papers. If you worked out an example, but did not include it in a publication, you can let the student generalize it.

What you should not do is ask a student a problem you are really interested in. First the student will be frustrated, because the problem is too hard for him, then you will be frustrated, because you will spend much more time explaining things to him then you would need to find the results for yourself, and finally everyone is frustrated, because you find an answer and have to explain it to the student.

Jan-Christoph Schlage-Puchta's user avatar

  • 3 "Every textbook contains the theorem that X implies Y, and every expert knows that quasi-X already suffices, but noone bothered to write it up." Are there a lot of things like that just lying around? For example? –  BCLC Commented Jul 30, 2015 at 16:03
  • 1 If someone proves a result, which only serves as a tool, the conditions are quite often too restrictive. For example, Hilbert space is used where reflexive Banach space suffices, or compact can often be replaced by countably compact. In number theory you can look at older paper using exponential sums, and see what improvements for the latter yield in the application. –  Jan-Christoph Schlage-Puchta Commented Jul 31, 2015 at 16:59
  • Jan-Christoph Schlage-Puchta, "the conditions are quite often too restrictive", do you mean it wouldn't be of interest to many mathematicians anyway? –  BCLC Commented Aug 5, 2015 at 12:04
  • 3 When talking about topics for a Bachelor or Master thesis, I think about problems which are open in the sense that they are not published, but solved in the sense that every expert in the area could immediately write down a proof. So I don't think these questions are interesting to other people. –  Jan-Christoph Schlage-Puchta Commented Aug 10, 2015 at 7:51
  • 1 @JackBauer Most of the work is in figuring out what these things are. If I had an example which I knew well enough to cite it here, probably somebody would have proved it. –  Ben Webster Commented Aug 11, 2015 at 17:17

Yes, undergraduates frequently prove new things, in the sense that every year there are new, publishable results proved by undergraduates. So, although a relatively small number of undergraduate math students participate in true "research", there are certainly students who are able to make nontrivial discoveries as undergraduates, and more than one might initially think. I have been at prestigious research schools and at anti-prestigious regional universites in the U.S.A. At every school I have been, there were undergraduates in mathematics with the aptitude for publishable research. The talent needed may not be "common", but it is certainly not "rare". The obstacles are primarily cultural, not intellectual.

The topic of undergraduate research has also been the subject of a question on MathOverflow , which makes for good reading.

For an example from personal experience: I recently published a peer-reviewed paper in what I consider to be a high-quality journal (and which is not in any way a "student" journal), with an undergraduate student co-author, who discovered the proof of one of the main theorems on his own between two of our research meetings.

Another example is the journal Involve , which is devoted to genuine student research. From their self-description :

Involve showcases and encourages high-quality mathematical research involving students from all academic levels. The editorial board consists of mathematical scientists committed to nurturing student participation in research. Submissions in all mathematical areas are encouraged. All manuscripts accepted for publication in Involve are considered publishable in quality journals in their respective fields, and include a minimum of one-third student authorship. Submissions should include substantial faculty input; faculty co-authorship is strongly encouraged. In most cases, the submission (and accompanying cover letter) should come from a faculty member. Involve, bridging the gap between the extremes of purely undergraduate-research journals and mainstream research journals, provides a venue to mathematicians wishing to encourage the creative involvement of students.

One thing that undergraduates are unlikely to have is the breadth of knowledge that is expected for PhD recipients. Particularly in mathematics, PhD students are examined in a range of subjects, and are expected to have mastered large parts of the undergraduate curriculum. Undergraduate research often involves learning enough about one particular area to prove new theorems. The student still needs to spend time learning other areas to have the knowledge expected of a PhD.

The real key for undergraduates who are looking to do publishable research is to find a collaboration with a good faculty mentor. Independent research by undergraduates is indeed quite rare (in fact, the majority of mathematics papers currently published have two or more authors - even experts benefit from collaboration). The MathOverflow thread linked above has more advice from other mathematicians.

Community's user avatar

  • 1 Thanks Oswald. Your example is kind of strange. WOuld your undergraduate co-author even have the opportunity to do such if not for knowing you? –  BCLC Commented Jul 29, 2015 at 18:41
  • 1 Perhaps I should have said: I heard a PhD is like an original contribution or something. Doesn't proving something new kind of amount to an original contribution? Again, I understand this may seem stupid. –  BCLC Commented Jul 29, 2015 at 18:42
  • 5 I wouldn't say undergraduates frequently prove new things, especially not in pure math. A small number of math undergraduates do serious research and even fewer make major contributions to the work. Most undergraduates hardly have the mathematical chops and insight to make major contributions simply due to lack of enough exposure. –  Cameron Williams Commented Jul 29, 2015 at 19:06
  • 2 I respectfully disagree. I'm saying that you're way over-inflating how successful undergraduate students are and my guess is that it's because you've worked with some very successful ones. My point is that on average, so very few that actually do research make contributions. Hell, successful PhD students maybe end up with only one or two papers by the time they're finished. –  Cameron Williams Commented Jul 29, 2015 at 19:47
  • 5 So far, I've worked with three (sets of) students at a non-selective school, resulting in three peer-reviewed papers that, in their journals, are indistinguishable from any other research. The students all met the usual standards for co-authorship. (This record is partially because, as a researcher, I know enough to pick math problems where we are likely to find publishable contributions.) When I was at prestigious research schools, I saw even more math majors who would have been able to work on publishable research as undergrads. As I wrote, the issue is much more culture than aptitude. –  Oswald Veblen Commented Jul 29, 2015 at 21:51

I can tell you my experience as I am currently writing an undergraduate thesis (though as a summer project).

I am an undergraduate student in mathematics currently doing a summer « introduction to research » internship. I'm studying probability theory.

As a first year student, about half of my time was spent solidifying my mathematical background in probability, measure theory and analysis. I also spent quite a lot of time studying specialised articles, and finally I applied the general theory I studied to a specific problem, where I did prove something « new », while very closely following other published results. On the way there, I also proved a few lemmas, that, while not of general interest, are « new » and interesting to me.

Clearly, undergraduate students are not expected to find groundbreaking results of general interest. However, they can contribute to mathematics by summarising and gathering related results from multiple articles, applying new theories, finding examples, etc.

A word of advice.

You should not aim for great discoveries, but rather simply try to do your own mathematics. Ask yourself a lot of « stupid » questions and find their answers. That's how you'll end up with a few small new results. Make sure you can grasp the big picture of your field of study, that you look at it from a critical standpoint and that you understand the issues that motivate it.

Do math undergraduates frequently prove new things?

Yes. But not great things, and sometimes things that might already be known to experts (but not widely accessible). I think that it is good enough for an undergrad to prove things that are new to him/her and her classmates/advisor/etc.

Olivier's user avatar

Some of the implicit premises of these sorts of questions, or the implicit premises in responses to the question, are really the issue. I would heartily agree that undergrads of all "calibers" should "be in the room" when something resembling "live" mathematics is being discussed. But/and this is most meaningful when we look at the falseness, artificiality, and sterility of the typical undergrad curriculum: it's fake and moribund, with no immediate room for anyone to do anything at all, and no hints about reality, either. Ghastly, yes. But that does not immediately entail a sort of "opposite", that novices need know very little to make meaningful contributions. Raw cleverness has already been exercised, quite systematically, for some hundreds of years (thousands?). People have learned useful things, and to not know these is to not know how to change a tire, or a light bulb, or a furnace filter, or open the door. Not that the usual curriculum helps much, either, I agree! But that does not mean that basic operational skills (involving occasionally subtle mathematics, literally, here) are irrelevant. Getting outside the degenerate "school math" thang is excellent... but thinking that that means "we don't need to know anything!" is obviously silly... even if appealing. "Complicated".

paul garrett's user avatar

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do maths degrees have dissertations

Think Student

Do All Degrees Have a Dissertation?

In General , University by Think Student Editor February 5, 2023 Leave a Comment

When thinking about university and the work you have to do, dissertations can often come to mind. As they’re an extended piece of writing, they can often feel long, hard, and simply too much of a hassle. Due to this, it’s entirely naturally to wonder if you must do one at all. That’s exactly what you’ll find out in this article.

In short, at undergraduate level, not all degrees will require you to have a dissertation. Whether you have to do a dissertation or not will generally depend on what you study and what university you study at.

However, at master’s degree level, you will need to do a dissertation to gain the full master’s degree. It may be possible for you to start the master’s degree and then to switch to a postgraduate certificate or diploma, which would not require you to do a dissertation.

Continue reading to learn more about dissertations and when you may need to do one. This article will tell you all you need to know about whether you have to do a dissertation and what the point of one is at all.

Table of Contents

Does everyone at university have to do a dissertation?

While university is often associated with traditional degrees, there are many other options for what you can study at university. These will generally be forms of higher education, meaning that they will be qualifications done after completing sixth form or college at level 4 or above. For more on higher education, check out this Think Student article .

The options of what you can study at a university can range from higher national certificates (HNCs) to foundation degrees and many more. For more on these, check out this UCAS guide .

Due to the wide range of qualifications that you can get at university, the answer is no, not everyone at university will have to do a dissertation . This is primarily due to how these higher education qualifications have different structures to the traditional bachelor’s or master’s degrees and so will often not require a dissertation.

For example, a HNC is equivalent to the first year of a bachelor’s degree. As a dissertation would generally be done in the final year of the degree, a dissertation couldn’t fit into its structure at all. For more on HNC qualifications, check out this article by University Compare.

Can you get a degree without doing a dissertation?

University can be hard to navigate, and it can be even harder trying to get your head around all of the terms and trying to figure out what a degree actually involves. Dissertations are a notorious part of the degree process, and you may wonder if they’re also an essential part.

In the UK, most degrees will require you to do a dissertation. However, this doesn’t apply to all degrees and will likely depend on where you go and what you study . To learn more about this, check out this article by Unite Students.

This means that it is entirely possible for you to get a degree without doing a dissertation as long as it’s not a compulsory part of your course. If the dissertation is something you feel strongly about not doing, then it can be worth fully looking at whether the courses you are interested in will make it compulsory in the modules section of course information pages.

For more insight into which subjects at undergraduate degree level are likely to require you to do a dissertation as well as if dissertations are compulsory at master’s degree level, check out the following headings.

Which degrees require a dissertation?

As mentioned above, in the UK, the majority of degrees will require you to do a dissertation. Otherwise, a dissertation or some other kind of research project may be an optional module that you can choose whether or not to take in your third year.

To find out more specific information about whether or not a specific course will require you to do a dissertation, it is best to look at the course information provided on the university’s website.

However, as a rule of thumb, it’s safe to assume that subjects that are based in both researching and writing will likely require you to do a dissertation . For example, history degrees are very likely to require you to do one.

Especially as at some universities they are considered a key part of the degree due to enabling you to put the skills you have developed into practice. For more on this, check out this page on the University of Southampton’s website.

Whereas more practical subjects, such as engineering, may instead get you to do a research or design project instead of a dissertation. In the same way, doing this kind of project instead will enable students to best apply the skills that they have learnt and developed during the course of their degree.

Do all master’s degrees require a dissertation?

During a master’s degree, students will typically learn about their subject area in greater depth to the extent that they pretty much become a “master” of it by the end of the degree. At level 7 (or level 11 in Scotland), master’s degrees are the second highest level of qualification you can get in the UK. To learn more about master’s degrees, check out this Think Student article .

Due to this, it’s no wonder that a range of high-level academic skills are involved and that you will have increased independence in your studies. As both of these are also traits that dissertations give you, you may be wondering if the master’s dissertation is essential.

The answer is yes, it is. In the UK, a master’s degree will require you to do a dissertation in order to complete your full master’s qualification.

However, if you start a master’s degree and are unable to do the dissertation, some universities will allow you to switch to a shorter postgraduate course, where you won’t have to do the dissertation. This may be a postgraduate certificate (PG Cert) or a postgraduate diploma (PG Dip).

To learn more about all of this, check out this guide by the University of York.

What is the point of a university dissertation?

In the UK, a dissertation is a massive research project and extended piece of writing that students undertake typically at the end of their degree, whether it is an undergraduate or master’s. To learn more about dissertations, check out this article by Think Student.

A dissertation allows a student to study the specific area of their subject that they are most interested in. This enables them to get more in-depth knowledge and to specialise in this element of their subject area. This can be especially great if you want to break into a specific career, related to this subject or if you want to study further.

Also, as a dissertation is done independently, it allows students to develop a wide range of skills from problem solving to time management to organisation. This means that a dissertation can enable students to come out of their studies not only with the degree and specialist knowledge in their subject area but also transferable skills that can improve their career prospects. To learn more about how doing a dissertation can improve your employability, check out this article by LSE.

While a dissertation can leave you will some valuable, transferable skills that can greatly enhance your career prospects and make it easier for you to integrate into a working environment, the dissertation alone may not be enough to secure you the graduate job you’re looking for. However, you can look at this Think Student article , which will give you some useful tips on how to find the right job for you after you graduate.

guest

Guide to Graduate Studies

The PhD Program The Ph.D. program of the Harvard Department of Mathematics is designed to help motivated students develop their understanding and enjoyment of mathematics. Enjoyment and understanding of the subject, as well as enthusiasm in teaching it, are greater when one is actively thinking about mathematics in one’s own way. For this reason, a Ph.D. dissertation involving some original research is a fundamental part of the program. The stages in this program may be described as follows:

  • Acquiring a broad basic knowledge of mathematics on which to build a future mathematical culture and more detailed knowledge of a field of specialization.
  • Choosing a field of specialization within mathematics and obtaining enough knowledge of this specialized field to arrive at the point of current thinking.
  • Making a first original contribution to mathematics within this chosen special area.

Students are expected to take the initiative in pacing themselves through the Ph.D. program. In theory, a future research mathematician should be able to go through all three stages with the help of only a good library. In practice, many of the more subtle aspects of mathematics, such as a sense of taste or relative importance and feeling for a particular subject, are primarily communicated by personal contact. In addition, it is not at all trivial to find one’s way through the ever-burgeoning literature of mathematics, and one can go through the stages outlined above with much less lost motion if one has some access to a group of older and more experienced mathematicians who can guide one’s reading, supplement it with seminars and courses, and evaluate one’s first attempts at research. The presence of other graduate students of comparable ability and level of enthusiasm is also very helpful.

University Requirements

The University requires a minimum of two years of academic residence (16 half-courses) for the Ph.D. degree. On the other hand, five years in residence is the maximum usually allowed by the department. Most students complete the Ph.D. in four or five years. Please review the program requirements timeline .

There is no prescribed set of course requirements, but students are required to register and enroll in four courses each term to maintain full-time status with the Harvard Kenneth C. Griffin Graduate School of Arts and Sciences.

Qualifying Exam

The department gives the qualifying examination at the beginning of the fall and spring terms. The qualifying examination covers algebra, algebraic geometry, algebraic topology, complex analysis, differential geometry, and real analysis. Students are required to take the exam at the beginning of the first term. More details about the qualifying exams can be found here .

Students are expected to pass the qualifying exam before the end of their second year. After passing the qualifying exam students are expected to find a Ph.D. dissertation advisor.

Minor Thesis

The minor thesis is complementary to the qualifying exam. In the course of mathematical research, students will inevitably encounter areas in which they have gaps in knowledge. The minor thesis is an exercise in confronting those gaps to learn what is necessary to understand a specific area of math. Students choose a topic outside their area of expertise and, working independently, learns it well and produces a written exposition of the subject.

The topic is selected in consultation with a faculty member, other than the student’s Ph.D. dissertation advisor, chosen by the student. The topic should not be in the area of the student’s Ph.D. dissertation. For example, students working in number theory might do a minor thesis in analysis or geometry. At the end of three weeks time (four if teaching), students submit to the faculty member a written account of the subject and are prepared to answer questions on the topic.

The minor thesis must be completed before the start of the third year in residence.

Language Exam

Mathematics is an international subject in which the principal languages are English, French, German, and Russian. Almost all important work is published in one of these four languages. Accordingly, students are required to demonstrate the ability to read mathematics in French, German, or Russian by passing a two-hour, written language examination. Students are asked to translate one page of mathematics into English with the help of a dictionary. Students may request to substitute the Italian language exam if it is relevant to their area of mathematics. The language requirement should be fulfilled by the end of the second year. For more information on the graduate program requirements, a timeline can be viewed at here .

Non-native English speakers who have received a Bachelor’s degree in mathematics from an institution where classes are taught in a language other than English may request to waive the language requirement.

Upon completion of the language exam and eight upper-level math courses, students can apply for a continuing Master’s Degree.

Teaching Requirement

Most research mathematicians are also university teachers. In preparation for this role, all students are required to participate in the department’s teaching apprenticeship program and to complete two semesters of classroom teaching experience, usually as a teaching fellow. During the teaching apprenticeship, students are paired with a member of the department’s teaching staff. Students attend some of the advisor’s classes and then prepare (with help) and present their own class, which will be videotaped. Apprentices will receive feedback both from the advisor and from members of the class.

Teaching fellows are responsible for teaching calculus to a class of about 25 undergraduates. They meet with their class three hours a week. They have a course assistant (an advanced undergraduate) to grade homework and to take a weekly problem session. Usually, there are several classes following the same syllabus and with common exams. A course head (a member of the department teaching staff) coordinates the various classes following the same syllabus and is available to advise teaching fellows. Other teaching options are available: graduate course assistantships for advanced math courses and tutorials for advanced undergraduate math concentrators.

Final Stages

How students proceed through the second and third stages of the program varies considerably among individuals. While preparing for the qualifying examination or immediately after, students should begin taking more advanced courses to help with choosing a field of specialization. Unless prepared to work independently, students should choose a field that falls within the interests of a member of the faculty who is willing to serve as dissertation advisor. Members of the faculty vary in the way that they go about dissertation supervision; some faculty members expect more initiative and independence than others and some variation in how busy they are with current advisees. Students should consider their own advising needs as well as the faculty member’s field when choosing an advisor. Students must take the initiative to ask a professor if she or he will act as a dissertation advisor. Students having difficulty deciding under whom to work, may want to spend a term reading under the direction of two or more faculty members simultaneously. The sooner students choose an advisor, the sooner they can begin research. Students should have a provisional advisor by the second year.

It is important to keep in mind that there is no technique for teaching students to have ideas. All that faculty can do is to provide an ambiance in which one’s nascent abilities and insights can blossom. Ph.D. dissertations vary enormously in quality, from hard exercises to highly original advances. Many good research mathematicians begin very slowly, and their dissertations and first few papers could be of minor interest. The ideal attitude is: (1) a love of the subject for its own sake, accompanied by inquisitiveness about things which aren’t known; and (2) a somewhat fatalistic attitude concerning “creative ability” and recognition that hard work is, in the end, much more important.

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Home > A&S > Math > MATH_GRADPROJ

Mathematics Graduate Projects and Theses

Theses/dissertations from 2023 2023.

Association of Lockdown Policies with COVID-19 Early Case Growth Rates in the United States , Anna Barefield

A History of the Hurwitz Problem Concerning Branched Coverings , James Alexander Byars

Theses/Dissertations from 2022 2022

Relationships Between COVID-19 Infection Rates, Healthcare Access, Socioeconomic Status, and Cultural Diversity , MarGhece P. J. Barnes

The Matrix Sortability Problem , Seth Cleaver

Cognitive Demand of Teacher-Created Mathematics Assessments , Megan Marie Schmidt

Waring Rank and Apolarity of Some Symmetric Polynomials , Max Brian Sullivan

Security Analysis of Lightweight Cryptographic Primitives , William Unger

Regression Analysis of Resilience and COVID-19 in Idaho Counties , Ishrat Zaman

Theses/Dissertations from 2021 2021

Tukey Morphisms Between Finite Binary Relations , Rhett Barton

A Data Adaptive Model for Retail Sales of Electricity , Johanna Marcelia

Exploring the Beginnings of Algebraic K-Theory , Sarah Schott

Zariski Geometries and Quantum Mechanics , Milan Zanussi

Theses/Dissertations from 2020 2020

The Directed Forest Complex of Cayley Graphs , Kennedy Courtney

Beliefs About Effective Instructional Practices Among Middle Grades Teachers of Mathematics , Lauren A. Dale

Analytic Solutions for Diffusion on Path Graphs and Its Application to the Modeling of the Evolution of Electrically Indiscernible Conformational States of Lysenin , K. Summer Ware

Theses/Dissertations from 2019 2019

Dynamic Sampling Versions of Popular SPC Charts for Big Data Analysis , Samuel Anyaso-Samuel

Computable Reducibility of Equivalence Relations , Marcello Gianni Krakoff

On the Fundamental Group of Plane Curve Complements , Mitchell Scofield

Radial Basis Function Finite Difference Approximations of the Laplace-Beltrami Operator , Sage Byron Shaw

Formally Verifying Peano Arithmetic , Morgan Sinclaire

Theses/Dissertations from 2018 2018

Selective Strong Screenability , Isaac Joseph Coombs

Mathematics Student Achievement in the Context of Idaho’s Advanced Opportunities Initiative , Nichole K. Hall

Secure MultiParty Protocol for Differentially-Private Data Release , Anthony Harris

Theses/Dissertations from 2017 2017

A Stable Algorithm for Divergence-Free and Curl-Free Radial Basis Functions in the Flat Limit , Kathryn Primrose Drake

The Classification Problem for Models of ZFC , Samuel Dworetzky

Joint Inversion of Compact Operators , James Ford

Trend and Return Level of Extreme Snow Events in New York City , Mintaek Lee

Multi-Rate Runge-Kutta-Chebyshev Time Stepping for Parabolic Equations on Adaptively Refined Meshes , Talin Mirzakhanian

Investigating College Instructors’ Methods of Differentiation and Derivatives in Calculus Classes , Wedad Mubaraki

The Random Graph and Reciprocity Laws , Spencer M. Nelson

Classification of Vertex-Transitive Structures , Stephanie Potter

Theses/Dissertations from 2016 2016

On the Conjugacy Problem for Automorphisms of Trees , Kyle Douglas Beserra

The Density Topology on the Reals with Analogues on Other Spaces , Stuart Nygard

Latin Squares and Their Applications to Cryptography , Nathan O. Schmidt

Solution Techniques and Error Analysis of General Classes of Partial Differential Equations , Wijayasinghe Arachchige Waruni Nisansala Wijayasinghe

Numerical Computing with Functions on the Sphere and Disk , Heather Denise Wilber

Theses/Dissertations from 2015 2015

The Classical Theory of Rearrangements , Monica Josue Agana

Nonlinear Partial Differential Equations, Their Solutions, and Properties , Prasanna Bandara

The Impact of a Quantitative Reasoning Instructional Approach to Linear Equations in Two Variables on Student Achievement and Student Thinking About Linearity , Paul Thomas Belue

Student Understanding of Function and Success in Calculus , Daniel I. Drlik

Monodromy Representation of the Braid Group , Phillip W. Hart

The Frobenius Problem , Anna Marie Megale

Theses/Dissertations from 2014 2014

Pi-1-1-determinacy and Sharps , Shehzad Ahmed

A Radial Basis Function Partition of Unity Method for Transport on the Sphere , Kevin Aiton

Diagrammatically Reducible 2-Complexes , Tyler Allyn

A Stochastic Parameter Regression Model for Long Memory Time Series , Rose Marie Ocker

Theses/Dissertations from 2013 2013

The Assignment Packet Grading System , Sarah Nichole Bruce

Using Learner-Generated Examples to Support Student Understanding of Functions , Martha Ottelia Dinkelman

Computing Curvature and Curvature Normals on Smooth Logically Cartesian Surface Meshes , John Thomas Hutchins

Schur's Theorem and Related Topics in Ramsey Theory , Summer Lynne Kisner

Theses/Dissertations from 2012 2012

On the Geometry of Virtual Knots , Rachel Elizabeth Byrd

A Stochastic Parameter Regression Approach for Time-Varying Relationship between Gold and Silver Prices , Birsen Canan-McGlone

Uncertainty Analysis of RELAP5-3D© , Alexandra E. Gertman and George L. Mesina

A Statistical Method for Regularizing Nonlinear Inverse Problems , Chad Clifton Hammerquist

Perfect Stripes from a General Turing Model in Different Geometries , Jean Tyson Schneider

Stability and Convergence for Nonlinear Partial Differential Equations , Oday Mohammed Waheeb

Regular Homotopy of Closed Curves on Surfaces , Katherine Kylee Zebedeo

Theses/Dissertations from 2011 2011

Coloring Problems , Thomas Antonio Charles Chartier

Modules Over Localized Group Rings for Groups Mapping Onto Free Groups , Nicholas Davidson

How Do We Help Students Interpret Contingency Tables? A Study on the Use of Proportional Reasoning as an Intervention , Kathleen M. Isaacson

A Fictitious Point Method for Handling Boundary Conditions in the RBF-FD Method , Joseph Lohmeier

Theses/Dissertations from 2010 2010

Developmental Understanding of the Equals Sign and Its Effects on Success in Algebra , Ryan W. Brown

The Inquiry Learning Model as an Approach to Mathematics Instruction , Michael C. Brune

Galois Theory for Differential Equations , Soheila Eghbali

Stably Free Modules Over the Klein Bottle , Andrew Misseldine

Combinatorics and Topology of Curves and Knots , Bailey Ann Ross

Theses/Dissertations from 2009 2009

Concept Booklets: Examining the Performance Effects of Journaling of Mathematics Course Concepts , Todd Stephen Fogdall

Effective Sample Size in Order Statistics of Correlated Data , Neill McGrath

Transparency in Formal Proof , Cap Petschulat

Weight Selection by Misfit Surfaces for Least Squares Estimation , Garrett Saunders

The Effects of a Standards-Based Mathematics Curriculum on the Self-Efficacy and Academic Achievement of Previously Unsuccessful Students , Cindy Chesley Shaw

Analytical Upstream Collocation Solution of a Quadratic Forced Steady-State Convection-Diffusion Equation , Eric Paul Smith

Solvability Characterizations of Pell Like Equations , Jason Smith

Theses/Dissertations from 2008 2008

Tube-Equivalence of Spanning Surfaces and Seifert Surfaces , Thomas Glass

Simple Tests for Short Memory in ARFIMA Models , Timothy A. C. Hughes

Incomparable Metrics on the Cantor Space , Trevor Jack

Richards' Equation and Its Constitutive Relations as a System of Differential-Algebraic Equations , Shannon K. Murray

Theses/Dissertations from 2007 2007

Theorem Proving in Elementary Analysis , Joanna Porter Guild

An Investigation of Lucas Sequences , Dustin E. Hinkel

A Canonical Countryman Line , William Russell Hudson

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Home > Computational, Mathematical, and Physical Sciences > Mathematics Education > Theses and Dissertations

Mathematics Education Theses and Dissertations

Theses/dissertations from 2024 2024.

Rigorous Verification of Stability of Ideal Gas Layers , Damian Anderson

Documentation of Norm Negotiation in a Secondary Mathematics Classroom , Michelle R. Bagley

New Mathematics Teachers' Goals, Orientations, and Resources that Influence Implementation of Principles Learned in Brigham Young University's Teacher Preparation Program , Caroline S. Gneiting

Theses/Dissertations from 2023 2023

Impact of Applying Visual Design Principles to Boardwork in a Mathematics Classroom , Jennifer Rose Canizales

Practicing Mathematics Teachers' Perspectives of Public Records in Their Classrooms , Sini Nicole White Graff

Parents' Perceptions of the Importance of Teaching Mathematics: A Q-Study , Ashlynn M. Holley

Engagement in Secondary Mathematics Group Work: A Student Perspective , Rachel H. Jorgenson

Theses/Dissertations from 2022 2022

Understanding College Students' Use of Written Feedback in Mathematics , Erin Loraine Carroll

Identity Work to Teach Mathematics for Social Justice , Navy B. Dixon

Developing a Quantitative Understanding of U-Substitution in First-Semester Calculus , Leilani Camille Heaton Fonbuena

The Perception of At-Risk Students on Caring Student-Teacher Relationships and Its Impact on Their Productive Disposition , Brittany Hopper

Variational and Covariational Reasoning of Students with Disabilities , Lauren Rigby

Structural Reasoning with Rational Expressions , Dana Steinhorst

Student-Created Learning Objects for Mathematics Renewable Assignments: The Potential Value They Bring to the Broader Community , Webster Wong

Theses/Dissertations from 2021 2021

Emotional Geographies of Beginning and Veteran Reformed Teachers in Mentor/Mentee Relationships , Emily Joan Adams

You Do Math Like a Girl: How Women Reason Mathematically Outside of Formal and School Mathematics Contexts , Katelyn C. Pyfer

Developing the Definite Integral and Accumulation Function Through Adding Up Pieces: A Hypothetical Learning Trajectory , Brinley Nichole Stevens

Theses/Dissertations from 2020 2020

Mathematical Identities of Students with Mathematics Learning Dis/abilities , Emma Lynn Holdaway

Teachers' Mathematical Meanings: Decisions for Teaching Geometric Reflections and Orientation of Figures , Porter Peterson Nielsen

Student Use of Mathematical Content Knowledge During Proof Production , Chelsey Lynn Van de Merwe

Theses/Dissertations from 2019 2019

Making Sense of the Equal Sign in Middle School Mathematics , Chelsea Lynn Dickson

Developing Understanding of the Chain Rule, Implicit Differentiation, and Related Rates: Towards a Hypothetical Learning Trajectory Rooted in Nested Multivariation , Haley Paige Jeppson

Secondary Preservice Mathematics Teachers' Curricular Reasoning , Kimber Anne Mathis

“Don’t Say Gay. We Say Dumb or Stupid”: Queering ProspectiveMathematics Teachers’ Discussions , Amy Saunders Ross

Aspects of Engaging Problem Contexts From Students' Perspectives , Tamara Kay Stark

Theses/Dissertations from 2018 2018

Addressing Pre-Service Teachers' Misconceptions About Confidence Intervals , Kiya Lynn Eliason

How Teacher Questions Affect the Development of a Potential Hybrid Space in a Classroom with Latina/o Students , Casandra Helen Job

Teacher Graphing Practices for Linear Functions in a Covariation-Based College Algebra Classroom , Konda Jo Luckau

Principles of Productivity Revealed from Secondary Mathematics Teachers' Discussions Around the Productiveness of Teacher Moves in Response to Teachable Moments , Kylie Victoria Palsky

Theses/Dissertations from 2017 2017

Curriculum Decisions and Reasoning of Middle School Teachers , Anand Mikel Bernard

Teacher Response to Instances of Student Thinking During Whole Class Discussion , Rachel Marie Bernard

Kyozaikenkyu: An In-Depth Look into Japanese Educators' Daily Planning Practices , Matthew David Melville

Analysis of Differential Equations Applications from the Coordination Class Perspective , Omar Antonio Naranjo Mayorga

Theses/Dissertations from 2016 2016

The Principles of Effective Teaching Student Teachershave the Opportunity to Learn in an AlternativeStudent Teaching Structure , Danielle Rose Divis

Insight into Student Conceptions of Proof , Steven Daniel Lauzon

Theses/Dissertations from 2015 2015

Teacher Participation and Motivation inProfessional Development , Krystal A. Hill

Student Evaluation of Mathematical Explanations in anInquiry-Based Mathematics Classroom , Ashley Burgess Hulet

English Learners' Participation in Mathematical Discourse , Lindsay Marie Merrill

Mathematical Interactions between Teachers and Students in the Finnish Mathematics Classroom , Paula Jeffery Prestwich

Parents and the Common Core State Standards for Mathematics , Rebecca Anne Roberts

Examining the Effects of College Algebra on Students' Mathematical Dispositions , Kevin Lee Watson

Problems Faced by Reform Oriented Novice Mathematics Teachers Utilizing a Traditional Curriculum , Tyler Joseph Winiecke

Academic and Peer Status in the Mathematical Life Stories of Students , Carol Ann Wise

Theses/Dissertations from 2014 2014

The Effect of Students' Mathematical Beliefs on Knowledge Transfer , Kristen Adams

Language Use in Mathematics Textbooks Written in English and Spanish , Kailie Ann Bertoch

Teachers' Curricular Reasoning and MKT in the Context of Algebra and Statistics , Kolby J. Gadd

Mathematical Telling in the Context of Teacher Interventions with Collaborative Groups , Brandon Kyle Singleton

An Investigation of How Preservice Teachers Design Mathematical Tasks , Elizabeth Karen Zwahlen

Theses/Dissertations from 2013 2013

Student Understanding of Limit and Continuity at a Point: A Look into Four Potentially Problematic Conceptions , Miriam Lynne Amatangelo

Exploring the Mathematical Knowledge for Teaching of Japanese Teachers , Ratu Jared R. T. Bukarau

Comparing Two Different Student Teaching Structures by Analyzing Conversations Between Student Teachers and Their Cooperating Teachers , Niccole Suzette Franc

Professional Development as a Community of Practice and Its Associated Influence on the Induction of a Beginning Mathematics Teacher , Savannah O. Steele

Types of Questions that Comprise a Teacher's Questioning Discourse in a Conceptually-Oriented Classroom , Keilani Stolk

Theses/Dissertations from 2012 2012

Student Teachers' Interactive Decisions with Respect to Student Mathematics Thinking , Jonathan J. Call

Manipulatives and the Growth of Mathematical Understanding , Stacie Joyce Gibbons

Learning Within a Computer-Assisted Instructional Environment: Effects on Multiplication Math Fact Mastery and Self-Efficacy in Elementary-Age Students , Loraine Jones Hanson

Mathematics Teacher Time Allocation , Ashley Martin Jones

Theses/Dissertations from 2011 2011

How Student Positioning Can Lead to Failure in Inquiry-based Classrooms , Kelly Beatrice Campbell

Teachers' Decisions to Use Student Input During Class Discussion , Heather Taylor Toponce

A Conceptual Framework for Student Understanding of Logarithms , Heather Rebecca Ambler Williams

Theses/Dissertations from 2010 2010

Growth in Students' Conceptions of Mathematical Induction , John David Gruver

Contextualized Motivation Theory (CMT): Intellectual Passion, Mathematical Need, Social Responsibility, and Personal Agency in Learning Mathematics , Janelle Marie Hart

Thinking on the Brink: Facilitating Student Teachers' Learning Through In-the-Moment Interjections , Travis L. Lemon

Understanding Teachers' Change Towards a Reform-Oriented Mathematics Classroom , Linnae Denise Williams

Theses/Dissertations from 2009 2009

A Comparison of Mathematical Discourse in Online and Face-to-Face Environments , Shawn D. Broderick

The Influence of Risk Taking on Student Creation of Mathematical Meaning: Contextual Risk Theory , Erin Nicole Houghtaling

Uncovering Transformative Experiences: A Case Study of the Transformations Made by one Teacher in a Mathematics Professional Development Program , Rachelle Myler Orsak

Theses/Dissertations from 2008 2008

Student Teacher Knowledge and Its Impact on Task Design , Tenille Cannon

How Eighth-Grade Students Estimate with Fractions , Audrey Linford Hanks

Similar but Different: The Complexities of Students' Mathematical Identities , Diane Skillicorn Hill

Choose Your Words: Refining What Counts as Mathematical Discourse in Students' Negotiation of Meaning for Rate of Change of Volume , Christine Johnson

Mathematics Student Teaching in Japan: A Multi-Case Study , Allison Turley Shwalb

Theses/Dissertations from 2007 2007

Applying Toulmin's Argumentation Framework to Explanations in a Reform Oriented Mathematics Class , Jennifer Alder Brinkerhoff

What Are Some of the Common Traits in the Thought Processes of Undergraduate Students Capable of Creating Proof? , Karen Malina Duff

Probing for Reasons: Presentations, Questions, Phases , Kellyn Nicole Farlow

One Problem, Two Contexts , Danielle L. Gigger

The Main Challenges that a Teacher-in-Transition Faces When Teaching a High School Geometry Class , Greg Brough Henry

Discovering the Derivative Can Be "Invigorating:" Mark's Journey to Understanding Instantaneous Velocity , Charity Ann Gardner Hyer

Theses/Dissertations from 2006 2006

How a Master Teacher Uses Questioning Within a Mathematical Discourse Community , Omel Angel Contreras

Determining High School Geometry Students' Geometric Understanding Using van Hiele Levels: Is There a Difference Between Standards-based Curriculum Students and NonStandards-based Curriculum Students? , Rebekah Loraine Genz

The Nature and Frequency of Mathematical Discussion During Lesson Study That Implemented the CMI Framework , Andrew Ray Glaze

Second Graders' Solution Strategies and Understanding of a Combination Problem , Tiffany Marie Hessing

What Does It Mean To Preservice Mathematics Teachers To Anticipate Student Responses? , Matthew M. Webb

Theses/Dissertations from 2005 2005

Fraction Multiplication and Division Image Change in Pre-Service Elementary Teachers , Jennifer J. Cluff

An Examination of the Role of Writing in Mathematics Instruction , Amy Jeppsen

Theses/Dissertations from 2004 2004

Reasoning About Motion: A Case Study , Tiffini Lynn Glaze

Theses/Dissertations from 2003 2003

An Analysis of the Influence of Lesson Study on Preservice Secondary Mathematics Teachers' View of Self-As Mathematics Expert , Julie Stafford

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SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Year 5 Undergraduate) AvailabilityNot available to visiting students
SCQF Credits40 ECTS Credits20
SummaryThis course is compulsory for MMath students in Year 5. It may also be taken in Year 4 by BSc/MA students who wish to undertake a challenging dissertation at masters level.

It may only be taken once and so should NOT be taken in Y4 by MMath students.

The Mathematics dissertation is an opportunity to research a subject in depth under the guidance of an experienced mathematician.

Work at Masters level is expected, and a good dissertation is expected to contain material that might be part of a monograph or a published paper in a refereed journal.

The normal assessment of the project is via a written report produced with LaTeX combined with a presentation delivered to an audience of advanced undergraduates.
Course description Not entered
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
---- call to this SRL ----
Course Delivery Information
Learning Outcomes
On completion of this course, the student will be able to:
Reading List
Dependent on topic.
Additional Information
Graduate Attributes and Skills Not entered
KeywordsMDiss
Contacts
Course organiserDr Milena Hering

[email protected]
Course secretaryMrs Alison Fairgrieve
(0131 6)50 5045
[email protected]
Navigation
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Other Information
 

do maths degrees have dissertations

  • Doing a PhD in Mathematics
  • Doing a PhD

What Does a PhD in Maths Involve?

Maths is a vast subject, both in breadth and in depth. As such, there’s a significant number of different areas you can research as a math student. These areas usually fall into one of three categories: pure mathematics, applied mathematics or statistics. Some examples of topics you can research are:

  • Number theory
  • Numerical analysis
  • String theory
  • Random matrix theory
  • Graph theory
  • Quantum mechanics
  • Statistical forecasting
  • Matroid theory
  • Control theory

Besides this, because maths focuses on addressing interdisciplinary real-world problems, you may work and collaborate with other STEM researchers. For example, your research topic may relate to:

  • Biomechanics and transport processes
  • Evidence-based medicine
  • Fluid dynamics
  • Financial mathematics
  • Machine learning
  • Theoretical and Computational Optimisation

What you do day-to-day will largely depend on your specific research topic. However, you’ll likely:

  • Continually read literature – This will be to help develop your knowledge and identify current gaps in the overall body of knowledge surrounding your research topic.
  • Undertake research specific to your topic – This can include defining ideas, proving theorems and identifying relationships between models.
  • Collect and analyse data – This could comprise developing computational models, running simulations and interpreting forecasts etc.
  • Liaise with others – This could take many forms. For example, you may work shoulder-to-shoulder with individuals from different disciplines supporting your research, e.g. Computer scientists for machine learning-based projects. Alternatively, you may need frequent input from those who supplied the data for your research, e.g. Financial institutions or biological research colleagues.
  • Attend a wide range of lectures, seminars and events.

Browse PhD Opportunities in Mathematics

Application of artificial intelligence to multiphysics problems in materials design, study of the human-vehicle interactions by a high-end dynamic driving simulator, physical layer algorithm design in 6g non-terrestrial communications, machine learning for autonomous robot exploration, detecting subtle but clinically significant cognitive change in an ageing population, how long does it take to get a phd in maths.

The average programme duration for a mathematics PhD in the UK is 3 to 4 years for a full-time studying. Although not all universities offer part-time maths PhD programmes, those that do have a typical programme duration of 5 to 7 years.

Again, although the exact arrangement will depend on the university, most maths doctorates will require you to first register for an MPhil . At the end of your first year, your supervisor will assess your progress to decide whether you should be registered for a PhD.

Additional Learning Modules

Best Universities for Maths PhD UK

Some Mathematics departments will require you to enrol on to taught modules as part of your programme. These are to help improve your knowledge and understanding of broader subjects within your field, for example, Fourier Analysis, Differential Geometry and Riemann Surfaces. Even if taught modules aren’t compulsory in several universities, your supervisor will still encourage you to attend them for your development.

Most UK universities will also have access to specialised mathematical training courses. The most common of these include Pure Mathematics courses hosted by Mathematics Access Grid Conferencing ( MAGIC ) and London Taught Course Centre ( LTCC ) and Statistics courses hosted by Academy for PhD Training in Statistics ( APTS ).

What Are the Typical Entry Requirements for A PhD in Maths?

In the UK, the typical entry requirements for a Maths PhD is an upper second-class (2:1) Master’s degree (or international equivalent) in Mathematics or Statistics [1] .

However, there is some variation on this. From writing, the lowest entry requirement is an upper second-class (2:1) Bachelor’s degree in any math-related subject. The highest entry requirement is a first-class (1st) honours Master’s degree in a Mathematics or Statistics degree only.

1st Class Honours Master’s degree. Degree must be in Mathematics or Statistics. 2:1 Master’s degree in Mathematics, Statistics or a closely related subject. 2:1 Bachelor’s degree in Mathematics, Statistics or a closely related subject.

It’s worth noting if you’re applying to a position which comes with funding provided directly by the Department, the entry requirements will usually be on the higher side because of their competitiveness.

In terms of English Language requirements, most mathematics departments require at least an overall IELTS (International English Language Testing System) score of 6.5, with no less than 6.0 in each individual subtest.

Tips to Consider when Making Your Application

When applying to any mathematics PhD, you’ll be expected to have a good understanding of both your subject field and the specific research topic you are applying to. To help show this, it’s advisable that you demonstrate recent engagement in your research topic. This could be by describing the significance of a research paper you recently read and outlining which parts interested you the most, and why. Additionally, you can discuss a recent mathematics event you attended and suggest ways in how what you learnt might apply to your research topic.

As with most STEM PhDs, most maths PhD professors prefer you to discuss your application with them directly before putting in a formal application. The benefits of this is two folds. First, you’ll get more information on what their department has to offer. Second, the supervisor can better discover your interest in the project and gauge whether you’d be a suitable candidate. Therefore, we encourage you to contact potential supervisors for positions you’re interested in before making any formal applications.

How Much Does a Maths PhD Typically Cost?

The typical tuition fee for a PhD in Maths in the UK is £4,407 per year for UK/EU students and £20,230 per year for international students. This, alongside the range in tuition fees you can expect, is summarised below:

UK/EU Full-Time £4,407 £4,327 – £8,589
UK/EU Part-Time £2,204 £2,164 – £4,295
International Full-Time £20,230 £15,950 – £24,531
International Part-Time £10,115 £7,975 – £12,266

Note: The above tuition fees are based on 12 UK Universities [1]  for 2020/21 Mathematic PhD positions. The typical fee has been taken as the median value.

In addition to the above, it’s not unheard of for research students to be charged a bench fee. In case you’re unfamiliar with a bench fee, it’s an annual fee additional to your tuition, which covers the cost of specialist equipment or resources associated with your research. This can include the upkeep of supercomputers you may use, training in specialist analysis software, or travelling to conferences. The exact fee will depend on your specific research topic; however, it should be minimal for most mathematic projects.

What Specific Funding Opportunities Are There for A PhD in Mathematics?

Alongside the usual funding opportunities available to all PhD Research students such as doctoral loans, departmental scholarships, there are a few other sources of funding available to math PhD students. Examples of these include:

You can find more information on these funding sources here: DiscoverPhDs funding guide .

What Specific Skills Do You Gain from Doing a PhD in Mathematics?

A doctorate in Mathematics not only demonstrates your commitment to continuous learning, but it also provides you with highly marketable skills. Besides subject-specific skills, you’ll also gain many transferable skills which will prove useful in almost all industries. A sample of these skills is listed below.

  • Logical ability to consider and analyse complex issues,
  • Commitment and persistence towards reaching research goals,
  • Outstanding verbal and written skills,
  • Strong attention to detail,
  • The ability to liaise with others from unique disciple backgrounds and work as part of a team
  • Holistic deduction and reasoning skills,
  • Forming and explaining mathematical and logical solutions to a wide range of real-world problems,
  • Exceptional numeracy skills.

What Jobs Can You Get with A Maths PhD?

Jobs for Maths PhDs - PhD in Mathematics Salary

One of the greatest benefits maths PostDocs will have is the ability to pursue a wide range of career paths. This is because all sciences are built on core principles which, to varying extents, are supported by the core principles of mathematics. As a result, it’s not uncommon to ask students what path they intend to follow after completing their degree and receive entirely different answers. Although not extensive by any means, the most common career paths Math PostDocs take are listed below:

  • Academia – Many individuals teach undergraduate students at the university they studied at or ones they gained ties to during their research. This path is usually the preferred among students who want to continue focusing on mathematical theories and concepts as part of their career.
  • Postdoctoral Researcher – Others continue researching with their University or with an independent organisation. This can be a popular path because of the opportunities it provides in collaborative working, supervising others, undertaking research and attending conferences etc.
  • Finance – Because of their deepened analytical skills, it’s no surprise that many PostDocs choose a career in finance. This involves working for some of the most significant players in the financial district in prime locations including London, Frankfurt and Hong Kong. Specific job titles can include Actuarial, Investment Analyst or Risk Modeller.
  • Computer Programming – Some students whose research involves computational mathematics launch their career as a computer programmer. Due to their background, they’ll typically work on specialised projects which require high levels of understanding on the problem at hand. For example, they may work with physicists and biomedical engineers to develop a software package that supports their more complex research.
  • Data Analyst – Those who enjoy number crunching and developing complex models often go into data analytics. This can involve various niches such as forecasting or optimisation, across various fields such as marketing and weather.

What Are Some of The Typical Employers Who Hire Maths PostDocs?

As mentioned above, there’s a high demand for skilled mathematicians and statisticians across a broad range of sectors. Some typical employers are:

  • Education – All UK and international universities
  • Governments – STFC and Department for Transport
  • Healthcare & Pharmaceuticals – NHS, GSK, Pfizer
  • Finance & Banking – e.g. Barclays Capital, PwC and J. P. Morgan
  • Computing – IBM, Microsoft and Facebook
  • Engineering – Boeing, Shell and Dyson

The above is only a small selection of employers. In reality, mathematic PostDocs can work in almost any industry, assuming the role is numerical-based or data-driven.

Math PhD Employer Logos

How Much Can You Earn with A PhD in Maths?

As a mathematics PhD PostDoc, your earning potential will mostly depend on your chosen career path. Due to the wide range of options, it’s impossible to provide an arbitrary value for the typical salary you can expect.

However, if you pursue one of the below paths or enter their respective industry, you can roughly expect to earn [3] :

Academic Lecturer

  • Approximately £30,000 – £35,000 starting salary
  • Approximately £40,000 with a few years experience
  • Approximately £45,000 – £55,000 with 10 years experience
  • Approximately £60,000 and over with significant experience and a leadership role. Certain academic positions can earn over £80,000 depending on the management duties.

Actuary or Finance

  • Approximately £35,000 starting salary
  • Approximately £45,000 – £55,000 with a few years experience
  • Approximately £70,000 and over with 10 years experience
  • Approximately £180,000 and above with significant experience and a leadership role.

Aerospace or Mechanical Engineering

  • Approximately £28,000 starting salary
  • Approximately £35,000 – £40,000 with a few years experience
  • Approximately £60,000 and over with 10 years experience

Data Analyst

  • Approximately £45,000 – £50,000 with a few years experience
  • Approximately £90,000 and above with significant experience and a leadership role.

Again, we stress that the above are indicative values only. Actual salaries will depend on the specific organisation and position and responsibilities of the individual.

Facts and Statistics About Maths PhD Holders

The below chart provides useful insight into the destination of Math PostDocs after completing their PhD. The most popular career paths from other of highest to lowest is education, information and communication, finance and scientific research, manufacturing and government.

Percentage of Math PostDocs entering an industry upon graduating

Note: The above chart is based on ‘UK Higher Education Leavers’ data [2] between 2012/13 and 2016/17 and contains a data size of 200 PostDocs. The data was obtained from the Higher Education Statistics Agency ( HESA ).

Which Noteworthy People Hold a PhD in Maths?

Alan turing.

Alan_Turing

Alan Turing was a British Mathematician, WW2 code-breaker and arguably the father of computer science. Alongside his lengthy list of achievements, Turning achieved a PhD in Mathematics at Princeton University, New Jersey. His thesis titled ‘Systems of Logic Based on Ordinals’ focused on the concepts of ordinal logic and relative computing; you can read it online here . To this day, Turning pioneering works continues to play a fundamental role in shaping the development of artificial intelligence (AI).

Ruth Lawrence

do maths degrees have dissertations

Ruth Lawrence is a famous British–Israeli Mathematician well known within the academic community. Lawrence earned her PhD in Mathematics from Oxford University at the young age of 17! Her work focused on algebraic topology and knot theory; you can read her interesting collection of research papers here . Among her many contributions to Maths, her most notable include the representation of the braid groups, more formally known as Lawrence–Krammer representations.

Emmy Noether

do maths degrees have dissertations

Emmy Noether was a German mathematician who received her PhD from the University of Erlangen, Germany. Her research has significantly contributed to both abstract algebra and theoretical physics. Additionally, she proved a groundbreaking theorem important to Albert Einstein’s general theory of relativity. In doing so, her theorem, Noether’s theorem , is regarded as one of the most influential developments in physics.

Other Useful Resources

Institute of Mathematics and its Applications (IMA) – IMA is the UK’s professional body for mathematicians. It contains a wide range of useful information, from the benefits of further education in Maths to details on grants and upcoming events.

Maths Careers – Math Careers is a site associated with IMA that provides a wide range of advice to mathematicians of all ages. It has a section dedicated to undergraduates and graduates and contains a handful of information about progressing into research.

Resources for Graduate Students – Produced by Dr Mak Tomford, this webpage contains an extensive collection of detailed advice for Mathematic PhD students. Although the site uses US terminology in places, don’t let that put you off as this resource will prove incredibly helpful in both applying to and undertaking your PhD.

Student Interviews – Still wondering whether a PhD is for you? If so, our collection of PhD interviews would be a great place to get an insider perspective. We’ve interviewed a wide range of PhD students across the UK to find out what doing a PhD is like, how it’s helped them and what advice they have for other prospective students who may be thinking of applying to one. You can read our insightful collection of interviews here .

[1] Universities used to determine the typical (median) and range of entry requirements and tuition fees for 2020/21 Mathematics PhD positions.

  • http://www.lse.ac.uk/study-at-lse/Graduate/Degree-programmes-2020/MPhilPhD-Mathematics
  • https://www.ox.ac.uk/admissions/graduate/courses/dphil-mathematics?wssl=1
  • https://www.graduate.study.cam.ac.uk/courses/directory/mapmpdpms
  • https://www.ucl.ac.uk/prospective-students/graduate/research-degrees/mathematics-mphil-phd
  • http://www.bristol.ac.uk/study/postgraduate/2020/sci/phd-mathematics/
  • https://www.surrey.ac.uk/postgraduate/mathematics-phd
  • https://www.maths.ed.ac.uk/school-of-mathematics/studying-here/pgr/phd-application
  • https://www.lancaster.ac.uk/study/postgraduate/postgraduate-courses/mathematics-phd/
  • https://www.sussex.ac.uk/study/phd/degrees/mathematics-phd
  • https://www.manchester.ac.uk/study/postgraduate-research/programmes/list/05325/phd-pure-mathematics/
  • https://warwick.ac.uk/study/postgraduate/research/courses-2020/mathematicsphd/
  • https://www.exeter.ac.uk/pg-research/degrees/mathematics/

[2] Higher Education Leavers Statistics: UK, 2016/17 – Outcomes by subject studied – https://www.hesa.ac.uk/news/28-06-2018/sfr250-higher-education-leaver-statistics-subjects

[3] Typical salaries have been extracted from a combination of the below resources. It should be noted that although every effort has been made to keep the reported salaries as relevant to Math PostDocs as possible (i.e. filtering for positions which specify a PhD qualification as one of their requirements/preferences), small inaccuracies may exist due to data availability.

Browse PhDs Now

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Mathematics Institute

Msc dissertations, mathematics dissertations.

The MSc dissertation counts for 90 CATS - that is, half of the total MSc load.

A dissertation is usually expository, collecting together results from several research papers into a coherent whole. Sometimes dissertations contain original research, and this is encouraged where appropriate. The general framework of a dissertation must be approved by the supervisor. This page may help to find staff members with interesting topics.

The appropriate length for a dissertation will vary with the topic, the formatting, and whether or not it includes figures, etc. As a guide, most MSc dissertations are between 30 and 50 A4 pages, double spaced, with normal font size and margins. Longer dissertations are not necessarily better, and the marks obtained depend much more on the quality of the content (especially the mathematics) than on the number of words. It is essential that the dissertation is well presented.

The dissertation should normally be produced in TEX or LaTEX. The package here is intended for PhD theses, but it can also be used for MSc dissertations. Suitable past dissertations are available for inspection. If you are in any doubt, please consult your supervisor or the Director of the MSc.

Interdisciplinary Mathematics Dissertations

For MSc Interdisciplinary Mathematics candidates the above holds, although these dissertations may be longer if they contain many diagrams, data or programs for example. The level of sophistication of the mathematics used in the dissertation may be lower than that expected in a straight Mathematics MSc provided that the dissertation demonstrates a compensating degree of understanding of the role or appropriate use of the mathematics described. The mathematics in the dissertation should be correct, appropriate for the interdisciplinary topic under discussion, and should say something of scientific value. This page may help to find staff members in the math dept with interesting topics.

Dissertation Marks

The dissertation is read by two internal examiners (including a supervisor) who report to the Examination Board. For MSc Interdisciplinary Mathematics dissertations, reports are generally requested from an internal examiner in each of the relevant departments to ensure sufficient interdisciplinary quality.

Examiners are asked to discuss the dissertation under the headings: Accuracy and depth of understanding (40%); Level of difficulty and degree of originality (40%); Exposition (10%); Context/Literature Bibliography (10%). The marks are passed to the Examination Board. The external examiner reviews the dissertations and marks prior to the Examination Board meeting.

The dissertation pass mark is 50% and students must pass the dissertation in order to pass the MSc.

Submitting your Dissertation or Postgraduate Diploma Project

The submission deadline is 2nd September 2024. Submissions will be made via Moodle. Further details will be provided closer to the deadline.

The name of the candidate's supervisor must be stated on the title page of the dissertation. The introduction to the dissertation should state clearly all sources used, and should pinpoint clearly any original passages claimed. The candidate should briefly describe how the sources were used and their relation to the dissertation. Acknowledgements should also appear, where appropriate, in the body of the dissertation. References with precise bibliographic details should be included. A dissertation will not be accepted if any reader (including one unfamiliar with the contents of the references cited) could gain a mistaken impression that expository material is the candidate's own original work.

Good English style, with correct grammar and spelling, is expected. The books Writing Mathematics Well by L. Gillman, and How to Write Mathematics by N.E. Steenrod et al. (AMS 1973) are recommended. (Both can be found in the Library catalogue .) In addition, supervisors can often help by suggesting which published mathematical papers are good models of exposition, and which are not.

Postgraduate Diploma Project

The expected standard in a Postgraduate Diploma is less than that for an MSc degree. If a candidate is recommended to transfer to the Postgraduate Diploma as a result of their examination results, the candidate will need to write a (Diploma) project rather than a dissertation. Students on the 2 year MSc course will submit a project at the end of their first year

The Diploma project counts for 24 CATS (rather than 90 CATS for an MSc dissertation). It is usually an expository work describing a piece of mathematics (which may be related to material covered in lectures). Sometimes a project may involve numerical work or a guided exploration of some particular problem. The project should normally be about 10-20 pages long and should show that the candidate is capable of writing about mathematics in a coherent fashion. The general framework of the project must be approved by the supervisor. The project is marked against these criteria and not against that for the MSc.

 
         
     

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Study Mathematics, why & how to study

Are you good with numbers do you want to develop a skillset that’s useful in various industries then a degree in mathematics could be for you..

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What’s Mathematics?

What mathematics degrees can you study, what do you need to get onto a mathematics degree, what topics does a mathematics degree cover, how will you be assessed, why study mathematics.

  • Are scholarships and bursaries available to students studying a Mathematics degree?

What do Mathematics graduates earn?

What jobs can you get as a mathematics graduate, what are the postgraduate opportunities, similar subjects to mathematics, have any questions, looking for clearing advice.

The Clearing concierge has the answers

Mathematics covers three main areas – maths, statistics and operational research. 

Mathematicians are interested in numbers, shape, and space. They simplify complex problems, classify objects, and prove that certain phenomena must, can or can’t happen.

Statistics is also driven by real-world problems. Statisticians examine data to help make predictions and decisions. This could be around drug efficacy or the likeliness of flooding, for instance.

Operational research (OR) is also known as management science. It is the analysis of decision-making processes. Some of its more well-known areas include game theory and the analysis of voting systems.

Take a look at the university league table for Mathematics .

Undergraduate degrees in Mathematics include single honours. You can also study it as a joint honours with a wide range of other subjects. Examples of degrees:

Mathematics BSc/BA/BMath

The BSc (Bachelor of Science) degree is the standard Mathematics degree. The BMath (Bachelor of Mathematics) is similar. The BA (Bachelor of Arts) has a more liberal arts focus, with a broader range of modules available.

Find Mathematics courses .

Actuarial Science and Mathematics BSc

These degree courses tend to combine the study of mathematics, statistics and business. They help you get ready to work as a professional actuary.

Search for Actuarial Science courses .

Applied Mathematics BSc

This degree helps you take theories of maths to apply them to real-world problems. Courses usually include plenty of computer and lab work. In the future, you could find work in fields like engineering, data analysis or technology.

Look through Applied Mathematics courses .

Mathematics, Operational Research, Statistics and Economics (MORSE) BMorse/MMorse

This interdisciplinary degree equips you with a specialist skillset. It prepares you for work where you apply quantitative and analytical methods to solve complex issues. The BMorse is undergraduate, whereas the MMorse includes an integrated master’s year.

Find MORSE courses .

Other options

There are many subject combinations you can study with maths. For instance:

  • Economics and Mathematics BSc
  • French and Mathematics BA
  • Mathematics and Philosophy BSc

Courses may include an integrated foundation year. Some offer opportunities for professional placements and studying abroad. Accelerated study and January start dates are often available too.

See the top 10 universities for Mathematics .

Entry requirements for a Mathematics degree range from 96–165 UCAS points. This could include the qualifications below:

  • A Levels: A*A*A–CCC (Further Maths is sometimes an essential requirement)  
  • BTECs: D*D*D*–MMM
  • Scottish Highers: AAAAA–BBBC (Advanced Highers: AAB–AA)
  • International Baccalaureate: 42–30
  • Universities will usually ask that you have studied: maths at A Level (or equivalent). Physics is also desirable. 
  • Some degrees require a maths admissions test, such as TMUA (Test of Mathematics for University Admission), STEP (Sixth Term Examination Paper), MAT (Mathematics Admissions Test) or Advanced Extension Award (AEA) 
  • Interview required by some universities 

Good to have

  • Research from books, journals, free lectures online, podcasts or the Maths Careers website (sponsored by the Institute of Mathematics and its Applications) to identify areas of interest
  • Work experience in a finance-related role
  • Participating in competitions or challenges such as the Senior Mathematical Challenge
  • Volunteering to help teach a maths class or tutor a homework club
  • STEM Summer schools, if eligible, such as UNIQ or Sutton Trust
  • Entry requirements
  • About UCAS points
  • Alternatives to A Levels

Typical modules for courses in this subject include:

  • Algebraic and differential geometry
  • Classical mechanics of particles
  • Electromagnetism, quantum mechanics and fluid dynamics
  • General relativity
  • Geometry and dynamics
  • Mathematical biology
  • Mathematical philosophy
  • Multivariate calculus and mathematical models
  • Probability and statistics
  • The mathematics of machine learning
  • Theoretical and statistical mechanics
  • Vector spaces 

Read about: what is STEM?

Assessment is mainly by written exam. Some modules may include a mixture of the following:

  • Poster presentation
  • Project report
  • Short written assignments

Mathematicians are needed in many professional contexts, from policymaking to medical research. Study the subject and your career could be involved in solving some of the world's many complex problems.

Career-specific skills:

  • Knowledge of the fundamentals of mathematics and topics that could include data science, quantum mechanics, computational modelling, mathematical ecology and epidemiology
  • Placements working in finance, statistics or modelling may be available on some courses

Transferable skills:

  • Communication
  • Creative problem solving
  • Decision making
  • Logical reasoning and analytical skills
  • Numeracy and IT skills
  • Presentation
  • Team working

Professional accreditation:

  • Degrees may be accredited by the Institute of Mathematics and its Applications (IMA). Accreditation leads towards Chartered Mathematician status (CMath)
  • Degrees with statistics may be accredited by the Royal Statistical Society (RSS)
  • Degrees with accountancy may offer accreditation with professional accountancy bodies. Accreditation leads to exemption from a range of professional accounting exams
  • Five reasons to study Mathematics

Are scholarships and bursaries available to students studying a Mathematics degree?  

Some universities offer students specific scholarships, bursaries, or grants to encourage access. It’s worth seeing if you are eligible, how to apply, and what it covers e.g., materials, tuition fees and/or living costs.  

Mathematics graduates can expect an entry-level salary of between £20,000–£28,000.

As your career progresses, your average salary will depend on the field you’ve entered. You could have an income of £55,000 as a senior actuarial analyst, or up to £156,500 as a chief actuary. If you become an operational researcher, you could earn from £40,000–£80,000 with experience.

Read more on what graduates do and earn .

Having specialist knowledge and skills will make you highly employable across many areas. Roles could include: 

  • Business analyst
  • Chartered accountant
  • Data scientist
  • Mathematical researcher
  • Mathematician
  • Radiation protection scientist
  • Statistician
  • Trainee actuary
  • Careers with a Mathematics degree

Graduates with a Mathematics degree need to complete teacher training such as a PGCE if they wish to become a teacher. Other postgraduate study offers the chance to specialise. Examples of postgraduate degrees include:

  • Applied Statistics and Datamining PGDip/MSc
  • Mathematical Modelling and Scientific Computing MSc
  • Mathematics DPhil/MPhil/PhD
  • Operational Research with Risk MSc
  • Pure Mathematics MSc
  • Find postgraduate courses for Mathematics
  • Types of postgraduate degrees

Other subject areas that might appeal to you include:

  • Accounting & Finance
  • Information Technology & Systems
  • Physics & Astronomy

Search for undergraduate Mathematics courses now!

If you’ve got any questions about studying Mathematics, you can email our experts at [email protected] . We’ll be happy to hear from you!

  • University rankings for Mathematics
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Dissertation in mathematics

This module enables you to carry out a sustained, guided, independent study of a topic in mathematics. There’s a choice of topics, for example: algebraic graph theory; aperiodic tilings and symbolic dynamics; advances in approximation theory; history of modern geometry; interfacial flows and microfluidics; variational methods, and Riemann surfaces. Provided study notes, books, research articles, and original sources guide you. You must master the appropriate mathematics and present your work as a final dissertation.

Qualifications

M840 is a compulsory module in our:

  • MSc in Mathematics (F04)
  • Credits measure the student workload required for the successful completion of a module or qualification.
  • One credit represents about 10 hours of study over the duration of the course.
  • You are awarded credits after you have successfully completed a module.
  • For example, if you study a 60-credit module and successfully pass it, you will be awarded 60 credits.
OU Postgraduate
SCQF 11
FHEQ 7

Find out more about entry requirements .

What you will study

The list of topics available varies each year. We’ll let MSc in Mathematics students know the available topics that October in the spring, before the module starts.

Recently available topics have included:

  • Advances in approximation theory
  • Algebraic graph theory
  • Aperiodic tilings and symbolic dynamics
  • History of modern geometry
  • Interfacial flows and microfluidics
  • Riemann surfaces
  • Variational methods.

Please note:

  • Since the available topics vary from year to year, check that we are offering the topic you wish to study before registering.
  • For staffing reasons, you might not be able to study your preferred topic. Therefore, we’ll ask you for your first and second choice. We can usually offer you one of your choices, although this cannot be guaranteed.

You will learn

Successful study of this module should enhance your skills in understanding complex mathematical texts, working on open-ended problems and communicating mathematical ideas clearly.

Teaching and assessment

Support from your tutor.

Throughout your module studies, you’ll get help and support from your assigned module tutor. They’ll help you by:

  • Marking your assignments (TMAs) and providing detailed feedback for you to improve.
  • Guiding you to additional learning resources.
  • Providing individual guidance, whether that’s for general study skills or specific module content.

The module has a dedicated and moderated forum where you can join in online discussions with your fellow students. There are also online module-wide tutorials. While these tutorials won’t be compulsory for you to complete the module, you’re strongly encouraged to take part. If you want to participate, you’ll likely need a headset with a microphone.

The assessment details can be found in the facts box.

Course work includes

Tutor-marked assignments (TMAs)

Future availability

Dissertation in mathematics (M840) starts once a year – in October.

This page describes the module that will start in October 2024.

We expect it to start for the last time in October 2029.

Regulations

Entry requirements.

You must have passed four modules from the MSc in Mathematics (F04) .

If you’ve passed only three modules, you may request exceptional permission to take M840 alongside another module.

Additionally:

  • To study the ‘Advances in approximation theory’ topic, you should have passed Advanced mathematical methods (M833) or the discontinued module M832.
  • To study the ‘Variational methods applied to eigenvalue problems’ topic, you should have passed Calculus of variations and advanced calculus (M820) .
  • To study the ‘Riemann surfaces’ topic, you should have a Grade 1 or 2 pass a course in Complex analysis (M337) or an equivalent course.

All teaching is in English and your proficiency in the English language should be adequate for the level of study you wish to take. We strongly recommend that students have achieved an IELTS (International English Language Testing System) score of at least 7. To assess your English language skills in relation to your proposed studies you can visit the IELTS website.

Start End England fee Register
05 Oct 2024 Jun 2025 £1360.00

Registration closes 05/09/24 (places subject to availability)

This module is expected to start for the last time in October 2029.

Additional costs

Study costs.

There may be extra costs on top of the tuition fee, such as set books, a computer and internet access.

Study events

This module may have an optional in-person study event. We’ll let you know if this event will take place and any associated costs as soon as we can.

Ways to pay for this module

We know there’s a lot to think about when choosing to study, not least how much it’s going to cost and how you can pay.

That’s why we keep our fees as low as possible and offer a range of flexible payment and funding options, including a postgraduate loan, if you study this module as part of an eligible qualification. To find out more, see Fees and funding .

Study materials

What's included.

You’ll have access to a module website, which includes:

  • a week-by-week study planner
  • course-specific module materials
  • audio and video content
  • assessment details and submission section
  • online tutorial access.

You will need

Some topics require specific books. We’ll let you know which once your topic is confirmed.

Computing requirements

You’ll need broadband internet access and a desktop or laptop computer with an up-to-date version of Windows (10 or 11) or macOS Ventura or higher.

Any additional software will be provided or is generally freely available.

To join in spoken conversations in tutorials, we recommend a wired headset (headphones/earphones with a built-in microphone).

Our module websites comply with web standards, and any modern browser is suitable for most activities.

Our OU Study mobile app will operate on all current, supported versions of Android and iOS. It’s not available on Kindle.

It’s also possible to access some module materials on a mobile phone, tablet device or Chromebook. However, as you may be asked to install additional software or use certain applications, you’ll also require a desktop or laptop, as described above.

If you have a disability

The material contains small print and diagrams, which may cause problems if you find reading text difficult. Adobe Portable Document Format (PDF) versions of printed material are available. Some Adobe PDF components may not be available or fully accessible using a screen reader and mathematical materials may be particularly difficult to read in this way. Alternative formats of the study materials may be available in the future.

To find out more about what kind of support and adjustments might be available, contact us or visit our disability support pages .

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Mathematics MSc dissertations

The Department of Mathematics and Statistics was host until 2014 to the MSc course in the Mathematics of Scientific and Industrial Computation (previously known as Numerical Solution of Differential Equations) and the MSc course in Mathematical and Numerical Modelling of the Atmosphere and Oceans. A selection of dissertation titles are listed below, some of which are available online:

2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991

2014: Mathematics of Scientific and Industrial Computation

Amanda Hynes - Slow and superfast diffusion of contaminant species through porous media

2014: Applicable and Numerical Mathematics

Emine Akkus - Estimating forecast error covariance matrices with ensembles

Rabindra Gurung - Numerical solution of an ODE system arising in photosynthesis

2013: Mathematics of Scientific and Industrial Computation

Zeinab Zargar - Modelling of Hot Water Flooding as an Enhanced Oil Recovery Method

Siti Mazulianawati Haji Majid - Numerical Approximation of Similarity in Nonlinear Diffusion Equations

2013: Mathematical and Numerical Modelling of the Atmosphere and Oceans

Yu Chau Lam - Drag and Momentum Fluxes Produced by Mountain Waves

Josie Dodd - A Moving Mesh Approach to Modelling the Grounding Line in Glaciology

2012: Mathematics of Scientific and Industrial Computation

Chris Louder - Mathematical Techniques of Image Processing

Jonathan Muir - Flux Modelling of Polynyas

Naomi Withey - Computer Simulations of Dipolar Fluids Using Ewald Summations

2012: Mathematical and Numerical Modelling of the Atmosphere and Oceans

Jean-Francois Vuillaume - Numerical prediction of flood plains using a Lagrangian approach

2011: Mathematics of Scientific and Industrial Computation

Tudor Ciochina - The Closest Point Method

Theodora Eleftheriou - Moving Mesh Methods Using Monitor Functions for the Porous Medium Equation

Melios Michael - Self-Consistent Field Calculations on a Variable Resolution Grid

2011: Mathematical and Numerical Modelling of the Atmosphere and Oceans

Peter Barnet - Rain Drop Growth by Collision and Coalescence

Matthew Edgington - Moving Mesh Methods for Semi-Linear Problems

Samuel Groth - Light Scattering by Penetrable Convex Polygons

Charlotte Kong - Comparison of Approximate Riemann Solvers

Amy Jackson - Estimation of Parameters in Traffic Flow Models Using Data Assimilation

Bruce Main - Solving Richards' Equation Using Fixed and Moving Mesh Schemes

Justin Prince - Fast Diffusion in Porous Media

Carl Svoboda - Reynolds Averaged Radiative Transfer Model

2010: Mathematics of Scientific and Industrial Computation

Tahnia Appasawmy - Wave Reflection and Trapping in a Two Dimensional Duct

Nicholas Bird - Univariate Aspects of Covariance Modelling within Operational Atmospheric Data Assimilation

Michael Conland - Numerical Approximation of a Quenching Problem

Katy Shearer - Mathematical Modelling of the regulation and uptake of dietary fats

Peter Westwood - A Moving Mesh Finite Element Approach for the Cahn-Hilliard Equation

Kam Wong - Accuracy of a Moving Mesh Numerical Method applied to the Self-similar Solution of Nonlinear PDEs

2010: Mathematical and Numerical Modelling of the Atmosphere and Oceans

James Barlow - Computation and Analysis of Baroclinic Rossby Wave Rays in the Atlantic and Pacific Oceans

Martin Conway - Heat Transfer in a Buried Pipe

Simon Driscoll - The Earth's Atmospheric Angular Momentum Budget and its Representation in Reanalysis Observation Datasets and Climate Models

George Fitton - A Comparative Study of Computational Methods in Cosmic Gas Dynamics Continued

Fay Luxford - Skewness of Atmospheric Flow Associated with a Wobbling Jetstream

Jesse Norris - A Semi-Analytic Approach to Baroclinic Instability on the African Easterly Jet

Robert J. Smith - Minimising Time-Stepping Errors in Numerical Models of the Atmosphere and Ocean

Amandeep Virdi - The Influence of the Agulhas Leakage on the Overturning Circulation from Momentum Balances

2009: Mathematics of Scientific and Industrial Computation

Charlotta Howarth - Integral Equation Formulations for Scattering Problems

David Fairbairn - Comparison of the Ensemble Transform Kalman Filter with the Ensemble Transform Kalman Smoother

Mark Payne - Mathematical Modelling of Platelet Signalling Pathways Mesh Generation and its application to Finite Element Methods

Mary Pham - Mesh Generation and its application to Finite Element Methods

Sarah Cole - Blow-up in a Chemotaxis Model Using a Moving Mesh Method

2009: Mathematical and Numerical Modelling of the Atmosphere and Oceans

Danila Volpi - Estimation of parameters in traffic flow models using data assimilation

Dale Partridge - Analysis and Computation of a Simple Glacier Model using Moving Grids

David MacLeod - Evaluation of precipitation over the Middle East and Mediterranean in high resolution climate models

Joanne Pocock - Ensemble Data Assimilation: How Many Members Do We Need?

Neeral Shah - Impact and implications of climate variability and change on glacier mass balance in Kenya

Tomos Roberts - Non-oscillatory interpolation for the Semi-Lagrangian scheme

Zak Kipling - Error growth in medium-range forecasting models

Zoe Gumm - Bragg Resonance by Ripple Beds

2008: Mathematics of Scientific and Industrial Computation

Muhammad Akram - Linear and Quadratic Finite Elements for a Moving Mesh Method

Andrew Ash - Examination of non-Time Harmonic Radio Waves Incident on Plasmas

Cassandra Moran - Harbour modelling and resonances

Elena Panti - Boundary Element Method for Heat Transfer in a Buried Pipe

Juri Parrinello - Modelling water uptake in rice using moving meshes

Ashley Twigger - Blow-up in the Nonlinear Schrodinger Equation Using an Adaptive Mesh Method

Chloe Ward - Numerical Evaluation of Oscillatory Integrals

Christopher Warner - Forward and Inverse Water-Wave Scattering by Topography

2008: Mathematical and Numerical Modelling of the Atmosphere and Oceans

Fawzi Al Busaidi - Fawzi Albusaidi

Christopher Bowden - A First Step Towards the Calculation of a Connectivity Matrix for the Great Barrier Reef

Evangelia-Maria Giannakopoulou - Flood Prediction and Uncertainty

Victoria Heighton - 'Every snowflake is different'

Thomas Jordan - Does Self-Organised Criticality Occur in the Tropical Convective System?

Gillian Morrison - Numerical Modelling of Tidal Bores using a Moving Mesh

Rachel Pritchard - Evaluation of Fractional Dispersion Models

2007: Numerical solution of differential equations

Tamsin Lee - New methods for approximating acoustic wave transmission through ducts (PDF 2.5MB)

Lee Morgan - Anomalous diffusion (PDF-1.5MB)

Keith Pham - Finite element modelling of multi-asset barrier options (PDF-3MB)

Alastair Radcliffe - Finite element modelling of the atmosphere using the shallow water equations (PDF-2.5MB)

Sanita Vetra - The computation of spectral representations for evolution PDE (PDF-3.2MB)

2007: Mathematical and numerical modelling of the atmosphere and oceans

Laura Baker - Properties of the ensemble Kalman filter (PDF-3.8MB)

Alison Brass - A moving mesh method for the discontinuous Galerkin finite element technique (PDF-916KB)

Daniel Lucas - Application of the phase/amplitude method to the study of trapped waves in the atmosphere and oceans (PDF-1.1MB)

Duduzile Nhlengethwa - Petrol or diesel (PDF-1MB)

Rhiannon Roberts - Modelling glacier flow (PDF-406KB)

David Skinner - A moving mesh finite element method for the shallow water equations (PDF-4.3MB)

Jovan Stojsavljevic - Investigation of waiting times in non-linear diffusion equations using a moving mesh method (PDF-538KB)

2006: Numerical solution of differential equations

Bonhi Bhattacharya - A moving finite element method for high order nonlinear diffusion problems

Jonathan Coleman - High frequency boundary element methods for scattering by complex polygons

Rachael England - The use of numerical methods in solving pricing problems for exotic financial derivatives with a stochastic volatility

Stefan King - Best fits with adjustable nodes and scale invariance

Edmund Ridley - Analysis of integral operators from scattering problems

Nicholas Robertson - A moving Lagrangian mesh model of a lava dome volcano and talus slope

2006: Mathematical and numerical modelling of the atmosphere and oceans

Iain Davison - Scale analysis of short term forecast errors

Richard Silveira - Electromagnetic scattering by simple ice crystal shapes

Nicola Stone - Development of a simplified adaptive finite element model of the Gulf Stream

Halina Watson - The behaviour of 4-D Var for a highly nonlinear system

2005: Numerical solution of differential equations

Jonathan Aitken - Data dependent mesh generation for peicewise linear interpolation

Stephen Arden - A collocation method for high frequency scattering by convex polygons

Shaun Benbow - Numerical methods for american options

Stewart Chidlow - Approximations to linear wave scattering by topography using an integral equation approach

Philip McLaughlin - Outdoor sound propagation and the boundary element method

Antonis Neochoritis - Numerical modelling of islands and capture zone size distributions in thin film growth

Kylie Osman - Numerical schemes for a non-linear diffusion problem

Shaun Potticary - Efficient evaluation of highly oscillatory integrals

Martyn Taylor - Investigation into how the reduction of length scales affects the flow of viscoelastic fluid in parallel plate geometries

Aanand Venkatramanan - American spread option pricing

2005: Mathematical and numerical modelling of the atmosphere and oceans

Richard Fruehmann - Ageostrophic wind storms in the central Caspian sea

Gemma Furness - Using optimal estimation theory for improved rainfall rates from polarization radar

Edward Hawkins - Vorticity extremes in numerical simulations of 2-D geostrophic turbulence

Robert Horton - Two dimensional turbulence in the atmosphere and oceans

David Livings - Aspects of the ensemble Kalman filter

David Sproson - Energetics and vertical structure of the thermohaline circulation

2004: Numerical solution of differential equations

Rakhib Ahmed - Numerical schemes applied to the Burgers and Buckley-Leverett equations

James Atkinson - Embedding methods for the numerical solution of convolution equations

Catherine Campbell-Grant - A comparative study of computational methods in cosmic gas dynamics

Paresh Prema - Numerical modelling of Island ripening

Mark Webber - The point source methods in inverse acoustic scattering

2004: Mathematical and numerical modelling of the atmosphere and oceans

Oliver Browne - Improving global glacier modelling by the inclusion of parameterised subgrid hypsometry within a three-dimensional, dynamical ice sheet model

Petros Dalakakis - Radar scattering by ice crystals

Eleanor Gosling - Flow through porous media: recovering permeability data from incomplete information by function fitting .

Sarah Grintzevitch - Heat waves: their climatic and biometeorological nature in two north american reigions

Helen Mansley - Dense water overflows and cascades

Polly Smith - Application of conservation laws with source terms to the shallow water equations and crowd dynamics

Peter Taylor - Application of parameter estimation to meteorology and food processing

2003: Numerical solution of differential equations

Kate Alexander - Investigation of a new macroscopic model of traffic flow

Luke Bennetts - An application of the re-iterated Galerkin approximation in 2-dimensions

Peter Spence - The Position of the free boundary formed between an expanding plasma and an electric field in differing geometries

Daniel Vollmer - Adaptive mesh refinement using subdivision of unstructured elements for conservation laws

2003: Mathematical and numerical modelling of the atmosphere and oceans

Clare Harris - The Valuation of weather derivatives using partial differential equations

Sarah Kew - Development of a 3D fractal cirrus model and its use in investigating the impact of cirrus inhomogeneity on radiation

Emma Quaile - Rotation dominated flow over a ridge

Jemma Shipton - Gravity waves in multilayer systems

2002: Numerical solution of differential equations

Winnie Chung - A Spectral Method for the Black Scholes Equations

Penny Marno - Crowded Macroscopic and Microscopic Models for Pedestrian Dynamics

Malachy McConnell - On the numerical solution of selected integrable non-linear wave equations

Stavri Mylona - An Application of Kepler's Problem to Formation Flying using the Störmer-Verlet Method

2002: Mathematical and numerical modelling of the atmosphere and oceans

Sarah Brodie - Numerical Modelling of Stratospheric Temperature Changes and their Possible Causes

Matt Sayer - Upper Ocean Variability in the Equatorial Pacific on Diurnal to Intra-seasonal Timescales

Laura Stanton - Linearising the Kepler problem for 4D-var Data Assimilation

2001: Numerical solution of differential equations

R.B. Brad - An Implementation of the Box Scheme for use on Transcritical Problems

D. Garwood - A Comparison of two approaches for the Approximating of 2-D Scattered Data, with Applications to Geological Modelling

R. Hawkes - Mesh Movement Algorithms for Non-linear Fisher-type Equations

P. Jelfs - Conjugate Gradients with Rational and Floating Point Arithmetic

M. Maisey - Vorticity Preserving Lax-Wendroff Type Schemes

C.A. Radcliffe - Positive Schemes for the Linear Advection Equation

2000: Numerical solution of differential equations

D. Brown - Two Data Assimilation Techniques for Linear Multi-input Systems.

S. Christodoulou - Finite Differences Applied to Stochastic Problems in Pricing Derivatives.

C. Freshwater - The Muskingum-Cunge Method for Flood Routing.

S.H. Man - Galerkin Methods for Coupled Integral Equations.

A. Laird - A New Method for Solving the 2-D Advection Equation.

T. McDowall - Finite Differences Applied to Joint Boundary Layer and Eigenvalue Problems.

M. Shahrill - Explicit Schemes for Finding Soliton Solutions of the Korteweg-de Vries Equation.

B. Weston - A Marker and Cell Solution of the Incompressible Navier-Stokes Equations for Free Surface Flow.

1999: Numerical solution of differential equations

M. Ariffin - Grid Equidistribution via Various Algorithmic Approaches.

S.J. Fletcher - Numerical Approximations to Bouyancy Advection in the Eddy Model.

N.Fulcher - The Finite Element Approximation of the Natural Frequencies of a Circular Drum.

V. Green - A Financial Model and Application of the Semi-Lagrangian Time-Stepping Scheme.

D.A. Parry - Construction of Symplectic Runge-Kutta Methods and their Potential for Molecular Dynamics Application.

S.C. Smith - The Evolution of Travelling Waves in a Simple Model for an Ionic Autocatalytic System

P. Swain - Numerical Investigations of Vorticity Preserving Lax-Wendroff Type Schemes.

M. Wakefield - Variational Methods for Upscaling.

1998: Numerical solution of differential equations

C.C. Anderson - A dual-porosity model for simulating the preferential movement of water in the unsaturated zone of a chalk aquifer.

K.W. Blake - Contour zoning.

M.R. Garvie - A comparison of cell-mapping techniques for basins of attraction.

W. Gaudin - HYDRA: a 3-d MPP Eulerian hydrocode.

D. Gnandi - Alternating direction implicit method applied to stochastic problems in derivative finance.

J. Hudson - Numerical techniques for conservation laws with source terms. .

H.S. Khela - The boundary integral method.

K. Singh - A comparison of numerical schemes for pricing bond options.

1997: Numerical solution of differential equations

R.V. Egan - Chaotic response of the Duffing equation. A numerical investigation into the dynamics of the non-linear vibration equation.

R.G. Higgs - Nonlinear diffusion in reservoir simulation.

P.B. Horrocks - Fokker-Planck model of stochastic acceleration: a study of finite difference schemes.

M.A. Wlasek - Variational data assimilation: a study.

1996: Numerical solution of differential equations

A. Barnes - Reaction-diffusion waves in an isothermal chemical system with a general order of autocatalysis.

S.J. Leary - Mesh movement and mesh subdivision.

S. McAllister - First and second order complex differential equations.

R.K. Sadhra - Investigating dynamical systems using the cell-to-cell mapping.

J.P. Wilson - A refined numerical model of sediment deposition on saltmarshes.

1995: Numerical solution of differential equations

M. Bishop - The modelling and analysis of the equations of motion of floating bodies on regular waves.

J. Olwoch - Isothermal autocatalytic reactions with an immobilized autocatalyst.

S. Stoke - Eulerian methods with a Lagrangian phase in gas dynamics.

R. Coad - 1-D and 2-D simulations of open channel flows using upwinding schemes.

1994: Numerical solution of differential equations

M. Ali - Application of control techniques to solving linear systems of equations .

M.H. Brookes - An investigation of a dual-porosity model for the simulation of unsaturated flow in a porous medium .

A.J. Crossley - Application of Roe's scheme to the shallow water equations on the sphere .

D.A. Kirkland - Huge singular values and the distance to instability. .

B.M. Neil - An investigation of the dynamics of several equidistribution schemes .

1993: Numerical solution of differential equations

P.A. Burton - Re-iterative methods for integral equations .

J.M. Hobbs - A moving finite element approach to semiconductor process modelling in 1-D. .

L.M. Whitfield - The application of optimal control theory to life cycle strategies .

S.J. Woolnough - A numerical model of sediment deposition on saltmarshes .

1992: Numerical solution of differential equations

I. MacDonald - The numerical solution of free surface/pressurized flow in pipes. .

A.D. Pollard - Preconditioned conjugate gradient methods for serial and parallel computers. .

C.J. Smith - Adaptive finite difference solutions for convection and convection-diffusion problems .

1991: Numerical solution of differential equations

K.J. Neylon - Block iterative methods for three-dimensional groundwater flow models .

  • Postgraduate study
  • Postgraduate taught courses

Mathematics

Explore this course:.

Applications for 2024 entry are now open. Apply now or register your interest to hear about postgraduate study and events at the University of Sheffield.

School of Mathematical and Physical Sciences , Faculty of Science

A maths lecturer at a blackboard

Course description

This one-year course is designed to help you build the foundations for a successful career in mathematics research. You'll have the freedom to choose from a variety of advanced lecture modules across pure and applied mathematics. Possible topics range from algebra, geometry and topology, to the ways that mathematics can be used in finance or studies of nature.

You'll be able to get valuable mathematics research experience by working with an experienced mathematician on a dissertation topic of your choice. Throughout the course, you'll have lots of opportunities to improve your problem solving and presentation skills, and learn how to create persuasive and logical arguments.

Specialist lectures have small class sizes so that they are more informal, with closer interactions between staff and students. We also have a directed reading module, individually tailored, to help you develop your understanding in the areas you're most interested in.

You'll be supported through regular meetings with your academic supervisor.

An open day gives you the best opportunity to hear first-hand from our current students and staff about our courses.

You may also be able to pre-book a department/school visit as part of a campus tour. Open days and campus tours

1 year full-time

You’ll be taught via a variety of lectures and small group seminars.

Our assessment methods are designed to support the achievement of learning outcomes and develop your professional skills. This includes coursework, exams and a dissertation.

Regular feedback is also provided, so you can understand your own development throughout the course.

Your career

The advanced topics you'll cover and the extensive research training make this course great preparation for a PhD. Sheffield maths graduates have secured postgraduate research positions at many of the world's top 100 universities.

Mathematics graduates also develop numerical, problem solving and data analysis skills that are useful in many careers. This can help you stand out in job markets where maths graduates thrive, such as computing, banking and data science.

Employers that have hired Sheffield maths graduates include Amazon, Barclays, Dell, Goldman Sachs, IBM, PwC, Sky, the NHS and the Civil Service.

School of Mathematical and Physical Sciences

A lecturer stood at the front of a seminar by a blackboard

The School of Mathematical and Physical Sciences is leading the way with groundbreaking research and innovative teaching. 

Our mathematicians and statisticians have expertise across pure mathematics, applied mathematics, probability and statistics. We focus on a variety of topics, from the most abstract questions in algebraic geometry and number theory, to the calculations behind infectious disease, black holes and climate change.

In the Research Excellence Framework 2021, 96 per cent of our mathematical sciences research was rated in the highest two categories as world-leading or internationally excellent.

We have strong links with the Society for Industrial and Applied Mathematics, the Institute of Mathematics and its Applications, the European Physical Society, and the International Society on General Relativity and Gravitation. With the support of the London Mathematical Society, we are also an organiser of the Transpennine Topology Triangle, a key focal point for topology research in the UK.

Mathematics and statistics staff have received honours from the Royal Society, the Society for Mathematical Biology and the Royal Statistical Society, who also provide professional accreditation for our statistics courses.

Student profiles

Bradley Ashley

The course offered great flexibility in fields of mathematics I had not yet seen

Bradley Ashley PhD student, University of Sheffield, Mathematics MSc

Bradley came to the University of Sheffield to do the Mathematics MSc, which prepared him for a PhD in pure mathematics.

Entry requirements

Minimum 2:1 undergraduate honours degree with a substantial maths component.

You can apply now using our Postgraduate Online Application Form. It's a quick and easy process.

More information

[email protected]

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Student at the Open University

Do They Do Dissertations, In The Open University Degrees?

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COMMENTS

  1. Dissertations

    OMMS and Part C students are required to undertake a dissertation worth two units as part of their degree programme. This can be either a mathematics dissertation or a statistics dissertation. The dissertation will entail investigating a topic in an area of the Mathematical Sciences under the guidance of a dissertation supervisor. This will ...

  2. Is it common for an undergraduate thesis in pure mathematics to prove

    Lastly, not many undergraduates in pure math do research because the gap they have to overcome between coursework and modern mathematics is pretty substantial. Those that make contributions in pure math are those that are very, very talented and have very thorough backgrounds (backgrounds that rival master's/PhD students).

  3. Dissertations

    Department of Mathematics. Science Center Room 325. 1 Oxford Street. Cambridge, MA 02138 USA. Tel: (617) 495-2171 Fax: (617) 495-5132. Department Main Office Contact. Web Site Contact. Digital Accessibility. Legacy Department of Mathematics Website.

  4. Do All Degrees Have a Dissertation?

    The answer is yes, it is. In the UK, a master's degree will require you to do a dissertation in order to complete your full master's qualification. However, if you start a master's degree and are unable to do the dissertation, some universities will allow you to switch to a shorter postgraduate course, where you won't have to do the ...

  5. Guide To Graduate Study

    For this reason, a Ph.D. dissertation involving some original research is a fundamental part of the program. The stages in this program may be described as follows: ... Non-native English speakers who have received a Bachelor's degree in mathematics from an institution where classes are taught in a language other than English may request to ...

  6. Mathematics Undergraduate Theses

    The Department of Mathematics offers Bachelor's degrees in Mathematics, Applied Mathematics, and Secondary Education Mathematics. In addition to mastering specific mathematical content, mathematics majors develop excellent general skills in problem solving and precise analytical thinking. Graduates of the program are prepared for more ...

  7. Mathematics Graduate Projects and Theses

    The Department of Mathematics offers Bachelor's degrees in Mathematics and Mathematics with Secondary Education option. A student's course of study can be tailored to suit a particular interest in pure mathematics, applied mathematics, mathematics teaching, or statistics. ... Theses/Dissertations from 2022 PDF. Relationships Between COVID ...

  8. Mathematics Education Theses and Dissertations

    Theses/Dissertations from 2020. Mathematical Identities of Students with Mathematics Learning Dis/abilities, Emma Lynn Holdaway. Teachers' Mathematical Meanings: Decisions for Teaching Geometric Reflections and Orientation of Figures, Porter Peterson Nielsen. Student Use of Mathematical Content Knowledge During Proof Production, Chelsey Lynn ...

  9. Course Catalogue

    Summary. This course is compulsory for MMath students in Year 5. It may also be taken in Year 4 by BSc/MA students who wish to undertake a challenging dissertation at masters level. It may only be taken once and so should NOT be taken in Y4 by MMath students. The Mathematics dissertation is an opportunity to research a subject in depth under ...

  10. Dissertation Topics Titles 2021-22

    History of Mathematics. Students wishing to do a dissertation based on the History of Mathematics are asked to contact Brigitte Stenhouse at [email protected] by Wednesday of week 1 with a short draft proposal. All decisions will be communicated to students by the end of week 2.

  11. Theses and dissertations

    A selection of PhD theses and MSc dissertations are available for you to read: mathematics PhD theses. statistics PhD theses. mathematics MSc dissertations. Department of.

  12. PhD in Mathematics

    In the UK, the typical entry requirements for a Maths PhD is an upper second-class (2:1) Master's degree (or international equivalent) in Mathematics or Statistics [1]. However, there is some variation on this. From writing, the lowest entry requirement is an upper second-class (2:1) Bachelor's degree in any math-related subject.

  13. MSc Dissertations

    As a guide, most MSc dissertations are between 30 and 50 A4 pages, double spaced, with normal font size and margins. Longer dissertations are not necessarily better, and the marks obtained depend much more on the quality of the content (especially the mathematics) than on the number of words. It is essential that the dissertation is well presented.

  14. Graduate Studies in Mathematics

    Our department offers Masters degrees in Mathematics, Applied Mathematics, and Statistics as well as a Ph.D. Degree in Mathematics, which can have an emphasis in any of the three areas mentioned. ... The M.S. in Data Science (MSDS) program is a professional, non-thesis degree that is jointly offered by the Mathematics and Computer Science ...

  15. PDF Mathematical and Statistical Dissertations in Part C Mathematics Part C

    The dissertation must be word-processed and have a font size of 12pt. The text may be single spaced. The dissertation should have a title page which includes the following: { the title of the dissertation, { the candidate's examination number, { the title of the candidate's degree course, { the term and year of submission.

  16. Mathematics degrees

    See the top 10 universities for Mathematics. What do you need to get onto a Mathematics degree? Must have. Entry requirements for a Mathematics degree range from 96-165 UCAS points. This could include the qualifications below: A Levels: A*A*A-CCC (Further Maths is sometimes an essential requirement) BTECs: D*D*D*-MMM

  17. M840

    Dissertation in mathematics. This module enables you to carry out a sustained, guided, independent study of a topic in mathematics. There's a choice of topics, for example: algebraic graph theory; aperiodic tilings and symbolic dynamics; advances in approximation theory; history of modern geometry; interfacial flows and microfluidics ...

  18. Mathematics MSc dissertations

    A selection of dissertation titles are listed below, some of which are available online: 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991. 2014: Mathematics of Scientific and Industrial Computation. Amanda Hynes - Slow and superfast diffusion of contaminant species through porous ...

  19. Mathematics MSc

    The advanced topics you'll cover and the extensive research training make this course great preparation for a PhD. Sheffield maths graduates have secured postgraduate research positions at many of the world's top 100 universities. Mathematics graduates also develop numerical, problem solving and data analysis skills that are useful in many careers.

  20. Have master's in math and can't find a job? : r/math

    Say "I taught myself Python in order to do the following for my thesis." The latter is more accurate, more informative, and not self-deprecating. ... If you have a degree in pure mathematics you shouldn't find it too hard to acquire skills in applied mathematics, statistics, and computer science. The biggest advantage a pure mathematician ...

  21. MSc without Dissertation?

    All master's degrees have a research component. There are postgraduate diplomas which do not have a research component (i.e. just the taught part of the master's degree), but ultimately the entire purpose of higher education is the development of independent critical thought, no matter what the discipline (i.e. getting a doctor to the required level so they can practice safely on their own or ...

  22. Does everyone have to do a dissertation?

    Hope this has made sense, thanks. (edited 12 years ago) Reply 1. 12 years ago. River85. No, not all students take a dissertation module in their final year, though most do. Other options including extended essays or short dissertations are common alternatives, particularly in Joint Honours programmes.

  23. Do They Do Dissertations, In The Open University Degrees?

    A. Blou17. Most named degrees have a compulsory project module. Doing a named OU degree not an easy way out of writing a dissertation.m If you want an "Open" degree then I guess you could skip the project component, but most level 3 courses will involved writing with a significant word count, in essay subjects. Reply 7.

  24. Do most degrees involve dissertations? : r/UniUK

    Most do, but they're not always mandatory. Maths often doesn't. In STEM a lot of ppl don't depending on ur degree. For example I do a straight science and most ppl did an investigative honours project (experiment and then write up in scientific paper style) but u could do a diss if u wanted.