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Southern Methodist University

Computational and theoretical chemistry at smu.

Since August 2017, SMU has offered a unique PhD program that provides students a specialized, comprehensive graduate education and degree in the burgeoning field of Theoretical and Computational Chemistry (TCC). It’s based on a comprehensive four-year degree plan that includes: 

core classes, 

electives, 

research, 

workshops 

and individual mentoring. 

This guide will help you explore interdisciplinary chemistry and get to know the cutting-edge research being conducted in the department at SMU, largely made possible with access to state-of-the-art resources and institutional support. You will also meet our expert faculty and discover what current and former students have to say about their experiences in the program. 

Chemistry: The Central Science 

Chemistry has long been known as the central science because it bridges the gap between the physical and life sciences, and the applied sciences (like engineering, environmental science and medicine). It is both “the central science” and the most foundational of the sciences since every other field of science relies on chemical insights into the nature of atoms and molecules in order to understand how more complex systems operate. 

Learn more about the history of theoretical and computational chemistry.

Chemistry and Key Economic Sectors

Because of its centrality and its role in transformative innovation, Chemistry is at the heart of many key economic sectors. The energy, technology, health and materials sectors all rely on chemical insight to advance, improve and deliver high quality products that support human flourishing. In addition, Chemistry plays a central, if not to say leading, role in initiating, carrying out and supporting developments that help guarantee the sustainability of our world.

The reliance of key economic sectors on chemistry means that there is a significant federal and industry investment in the development of top-notch chemists and significant opportunity for chemists to thrive in the many roles available to them in different fields. 

Chemistry and the Human Experience of the World

Chemistry plays a central role in our world. In particular, TCC applies quantum mechanics and molecular modeling, along with modern tools, such as machine learning, to improve our lives and increase sustainability in many important areas:

Development of new drugs to fight cancer, Alzheimer’s, Parkinson’s, Malaria

Design of new catalysts, solar energy collector materials, hydrogen generation, biofuels

Materials and processes for filtering and cleaning water

Development of novel materials, nanotechnology, quantum computing, semiconductor technology, etc.

The Importance of an Interdisciplinary Approach to Chemistry Research

To fulfill its role and meet the requirements of our time, Chemistry has changed and adapted, becoming highly interdisciplinary and multidisciplinary with research topics that reach beyond traditional borders. As a result, the field is largely collaborative, making chemists ideal partners for researchers in medicine, biology, engineering, and environmental sciences. 

What Can You Do With a Chemistry PhD?

Chemists who seek jobs in TCC must have more than just a strong knowledge of basic chemistry. They should also be comfortable with various levels of chemistry programming and code development, have a good understanding of theoretical principles and be motivated problem-solvers. Additionally, familiarity with applying computer learning to research and experimental design is important.

A PhD in Chemistry from SMU opens the door for a wide range of career choices in both academia and industry, including government and national laboratories. Some potential career paths for chemistry PhDs include:

Forensic chemistry

Government (Research)

Industrial research (R&D)

IT companies

Postsecondary education

Product development

Tech/biotech start-ups

Understanding the Value of Theoretical and Computational Chemistry and its Relationship to Traditional Chemistry

What is theoretical chemistry.

Theoretical Chemistry is a branch of Chemistry that uses conceptual theories derived from physics and mathematics to explain and generalize the rules that govern all chemical systems and interactions. It involves the development of computational and theoretical methods based on quantum chemistry and mathematical procedures in order to describe the physical properties and the chemical behavior of atoms and molecules. 

Theoretical Chemistry comprises several disciplines such as:

• Quantum Chemistry

Molecular Mechanics 

Statistical Mechanics 

Nonlinear Thermodynamics

Among these disciplines under Theoretical Chemistry, Quantum Chemistry is by far the most popular field. There are thousands of investigations and research projects carried out every year in this field.

What is Computational Chemistry?

Although the terms Theoretical Chemistry and Computational Chemistry are very often used synonymously, the fields are not identical. Computational Chemistry takes the conceptual framework of Theoretical Chemistry and allows the insights and questions of Theoretical Chemistry to be rigorously tested, modeled, and observed by running programs on high-performance super computers. 

Computational Chemistry requires a strong understanding of theory, but also the ability to translate theoretical methods into suitable computer programs so that chemical problems can be solved.

The Partnership Between Traditional and Computational Chemistry

The primary goal of Chemistry is to control chemical reactions with the purpose of generating useful, non-toxic, and non-dangerous materials with desirable properties in an economic way.

Computational Chemistry is a discipline of chemistry that can substantially contribute to all the fields of science as well as the metamorphosis of traditional to modern Chemistry. 

Computational chemistry with quantum chemistry, molecular modeling, and molecular dynamics as its major tools has matured and become an important partner of experimental chemistry in the last decades. These computational tools are used to shorten and facilitate chemical discovery processes, avoid costly and/or dangerous experiments, and obtain information not amenable to experiment.

All work of the Department of Chemistry at SMU has as a common goal to understand the electronic structure of molecules so that reliable predictions of their properties and chemical behavior can be made. These predictions become important in all those cases where chemical experiments are not conclusive, too dangerous, too costly or not possible at all.

Computational Chemistry makes advances that are beyond the possibility of traditional chemistry, but relies on input from other branches of science to inform the relevance of its modeling efforts. This is one of the major reasons the Department of Chemistry at SMU emphasizes an interdisciplinary approach to teaching and research.

Exploring Theoretical and Computational Chemistry Research Topics

The Department of Chemistry’s research at SMU focuses on the large-molecule world, concentrating on biomolecules, engaging in drug design and introducing computational nanotechnology:

• Molecular Mechanics
• Molecular Modeling
• Statistical Mechanics
• Nonlinear Thermodynamic

Current Research Interests

• Cracking the second code of life through protein dynamics using artificial intelligence and data science approaches. Deciphering enzyme catalysis and evolution through multi-scale simulations and theoretical framework development. Employing computational methodologies to solve many more real-world chemistry and biology problems. Training a new generation of scientists and workforce with a broad range of problem solving, analytical, and computer programing skills.
• Application of ab initio (meaning “from the beginning”) methods based on quantum mechanics and combining concepts and techniques from chemistry, physics, mathematics, and computer science to use and develop accurate theoretical methods to study molecules, reactions, clusters, and extended systems; active areas include computational spectroscopy (specifically X-ray), computational techniques for tensor contraction and factorization, and development of new theoretical methods. 
• Enhance drug design through our novel artificial-intelligence-supported, computer-assisted platform with emphasis on covalent binder and enzyme drugs being described with our automated protein structure analysis software.

SMU: An Ideal Home for Research of this Kind

SMU is a private, highly renowned research institution founded in 1911, committed to academic freedom and inclusivity. Because of our size, we are a community where you can build strong connections to faculty mentors and enjoy an individualized education that fits your research interests and career goals. 

Find out what life is really like in a chemistry research-intensive PhD program from a TCC graduate. 

High-Performance Computing

SMU excels in Theoretical and Computational Chemistry through a deep partnership with the Center for Research Computing which supports a state-of-the-art research computing infrastructure for SMU faculty and students. 

The cornerstone of our computational excellence is SMU’s high-performance computer cluster ManeFrame II which has a total capacity of 930 teraflops.

SMU is investing $11.5 million into a powerful new supercomputing research system featuring an NVIDIA DGX SuperPOD. The successor of ManeFrame II, ManeFrame III, is already in planning and will be launched in the Fall of 2022.

Connected with the NVIDIA Quantum InfiniBand networking platform in SMU's data center, it will produce a theoretical 100 petaflops of computing power enabling the university's network to perform "a blistering 100 quadrillion operations per second.

Competitive  Funding and the Student Experience

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Premiere research environment.

The Department of Chemistry is a vibrant, strongly research-oriented unit in Dedman College. Chemistry faculty have secured grants totaling nearly $10 million over the last 10 years, and have been honored with four NSF CAREER awards, an impressive record for a department of this size.

Access to a Thriving and Supportive Graduate Community

SMU’s Moody School of Graduate and Advanced Studies aims to provide opportunities for professional advancement and graduate student engagement through regular workshops and events. 

Students are able to find a variety of resources that can assist them at any stage of the doctoral process, whether it is working one-on-one with our Director of Fellowships and Awards to seek external grants for your work or connecting with an on-staff writing center counselor to help you revise your paper. Just as important, students can also meet with other grad students from across campus at monthly social events whenever they need a break from the lab. 

Location, Location, Location

Because of our location in Dallas, Texas, we have easy access to a number of diverse industries that are looking for creative and ingenious researchers. Dallas is one of the fastest-growing cities in the United States and is home to several technological and industrial businesses, both established and starting up. Forbes ranks Dallas as #2 in best places for business and careers, meaning there is lots of potential for new jobs as students enter the market. 

Our picturesque SMU campus is nestled just north of the bustling downtown area while still maintaining the feel of a small, intimate campus. From great restaurants and shopping to easily accessible public transportation near campus, the Dallas Metro area has a lot to offer graduate students who come here to take the next step in their professional career.

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Get to know the city of Dallas through our guide and learn what it is like to live, work, eat, study, and relax here while completing your graduate degree at SMU.

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The first rigorous theoretical and computational phd program in the us, theoretical and computational chemistry phd.

Students commit to a thorough and intensive full-time, four-year, 66-credit coursework plan that establishes the foundations of theory and computational topics and provides students the flexibility to explore their own innovative research. Teaching practicums and special topics are also incorporated into the curriculum to ensure that students are staying on top of the most recent trends and getting the practical experience necessary to be competitive candidates for both academic and industry jobs after graduation. 

Financial Support

In addition to professional support, our department is dedicated to providing substantial financial support that allows students to focus on their studies. 

Benefits include an annual stipend of $25,000, full tuition waiver, coverage of health insurance premiums, and a travel allowance for national conferences. Outstanding candidates are also eligible for competitive fellowships provided by the Moody School of Graduate and Advanced Studies and the Center for Research Computing that provide additional financial assistance. 

Get To Know the Moody School of Graduate and Advanced Studies

Access this guide to d iscover world-changing research, competitive funding, & professional and community engagement at SMU.

Learn More About the $100 Million Gift from the Moody Foundation

Our department has a uniquely high percentage of theoretical faculty, offering a broad and diverse spectrum of research, and leading to a unique opportunity for the TCC PhD students. We strive to create a vibrant, friendly, and supportive environment where students work on cutting-edge research with one of the four TCC faculty members. Furthermore, interdisciplinary research within the chemistry department and beyond is strongly encouraged.

Advantages in a Competitive Job Market

The demand for a highly trained computational and theoretical chemistry workforce is steadily increasing. The U.S. Bureau of Labor Statistics predicts there will be an annual increase of at least 15% for computational and theoretical chemistry positions until 2025, a faster growth rate than for all other chemistry-related jobs. SMU’s TCC PhD program provides you a pipeline to a wide range of academic and non-academic jobs requiring intellectual leadership and technical excellence. Our graduates are now at research centers such as Pacific Northwest National Labs and companies such as Google and Eli Lilly.

Faculty Profiles

Professor and chair elfi kraka.

Elfi Kraka leads the Computational and Theoretical Chemistry Group (CATCO) . CATCO’s research mission is to develop modern quantum chemical tools and to apply these tools to solve pending problems in chemistry, biology, materials science, and beyond. Special CATCO software includes the Local Mode Analysis (LModeA), a unique tool for decoding chemical information embedded in modern vibrational spectroscopy data, applied to both single molecules in gas phase, solution but also to periodic systems and crystals. The Unified Reaction Valley Approach (pURVA) describes a chemical reaction with an accuracy and a detail never achieved before. We have analyzed so far more than 700 homogenous catalysis reactions and the first enzyme reactions at the quantum chemical level to learn from Mother Nature how to design the next generation of catalysts. SSnet (Secondary Structure based End-to-End Learning) for protein-ligand Interaction prediction forms the basis for our new artificial intelligence supported computer assisted drug design platform stretching form screening billions of drugs candidates to the quantum chemical descriptions of the most promising candidates. Take a look at smu.edu/catco

Professor Doran Bennett

Doran Bennett heads the Mesoscience Lab, developing new computational tools at the intersection of chemistry, biology, physics, and applied mathematics. We are a tight-knit team that takes on big questions and develops new tools to accelerate scientific discovery. Intrigued by the biophysics of photosynthetic membranes? What about the role of quantum mechanics in how materials absorb and use light? You can learn more about the problems we are passionate about and the tools we develop at: www.mesosciencelab.com . 

Professor Peng Tao

The ultimate goal of Tao Research group is to decipher the deepest secrets in life science through fundamental and data-driven computational studies. The group develops advanced and novel biophysical theories and computational methods to solve challenging problems in life science to achieve this goal. They are currently exploring both functional and dynamical mechanisms of proteins using advanced machine learning methods.  This approach has led to a novel molecular evolutionary theory of enzymes. All group members work closely to form an open, friendly, supportive, and inspiring research and developing environment to help each other pursuing their career and personal goals. Webpage: faculty.smu.edu/ptao

Professor Devin Matthews

The Matthews group focuses on using and developing accurate theoretical methods to study molecules, reactions, clusters, and extended systems. We especially challenge ourselves to get “the right answer for the right reason” and to understand the Why and How of molecules and their reactions by bringing chemistry together with physics (the quantum world), biology (the molecular basis of life and health), mathematics (approximation, optimization, and analysis), and computer science (high-performance computing and machine learning). We are currently researching the use of equation-of-motion coupled cluster techniques for X-ray spectroscopies, with applications to the structure of liquids, disordered systems, and molecular dynamics, as well as ways in which highly accurate methods such as coupled cluster can be efficiently applied to large, complex molecules.  Visit us at matthewsresearchgroup.webstarts.com

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Student Testimonial

Where are you from? Where and what did you study during your undergraduate years? What initially got you interested in Chemistry as a field of study?

I’m from Dallas – I’ve lived in the area practically all my life. During undergrad at the University of Texas at Dallas, I honestly tried to study everything – for a (very short) while I was considering trying for a triple major in physics, chemistry, and biology (I figured out that was a bad idea after about one semester). My degree is in biochemistry, but I put enough work into my physics minor, with a focus on quantum and statistical physics, that it’s not unreasonable to say that my education was in physical chemistry (with a touch of music, my other minor). I’ve liked chemistry since high school, and it seemed like a fun and interesting field.

Did you encounter any hesitations, obstacles or fears about pursuing a PhD in TCC? If yes, what were these dilemmas and how did you overcome them?

There would probably be something very wrong with me if I didn’t have any hesitation or fear about spending four to five years of my life more-or-less hunched over a computer, spiraling into madness as I run endless simulations, in between the hardest classes I’ll ever have to take. I mean, there definitely is something wrong with me, but a lack of anxiety is not it. In the end, I realized that five years just isn’t that big of a deal – sure, I’ll be working myself to the bone, but it’s a satisfying kind of exhaustion, and my time will go toward making the world a better place – I honestly believe that science has the power to improve the world. If I decide that I never want to so much as look at a Python IDE again at the end of this program, I can do something else. It’s not as if immersing myself in method and algorithm development and heavy mathematics will limit my options.  My fear was losing a chunk of my life, and the resolution for me was that time spent working isn’t any more or less gone than time spent any other way.

How did you hear about the TCC PhD program at SMU and what specific features attracted you to this program when you were looking at graduate schools?

During undergrad, I was in an experimental protein engineering lab with the awesome Dr. Sheel Dodani (shameless advertising for my old group, but seriously, her work and lab are super cool) when I attended a talk by Dr. Doran I. G. Bennett of the MesoScience Lab. Dr. Bennett’s work focuses on taking intractable problems – loosely speaking, those that have system sizes that are typical of classical problems or heavily approximated quantum mechanics, but dynamics dependent on full, formally-exact quantum mechanics – and making them solvable. In essence, if you’ll forgive a little romanticization, we make the impossible possible. I liked what I saw, asked Dr. Bennett if I could jump on board, and never looked back.

Now that you’ve experienced the program, what do you most appreciate about it?

I find the work meaningful and the mentors excellent. Dr. Bennett’s lab philosophy – one that is more conscious of its students as growing scientists rather than tools – is what I hope to see universally in the labs of the future.

Tell me about some of the research you’ve done over the course of your years of study. What has been your favorite research project and why did you enjoy it?

My favorite research project so far was a week of sheer sleepless intensity. We set out as a lab to, over the course of 5 days, use our code to model excitation dynamics in a membrane of light-harvesting complex 2 (LHC2). The back-and-forth between sections of the lab – one half modeling the membrane itself, the other simulating the dynamics of photoexcitation – was an incredible experience. Not only was the goal ambitious, but the sheer ridiculous intensity of the work was extremely fun. With that said, I’m not keen on repeating that level of work for a while!

What are your career dreams or plans? How has the TCC PhD program at SMU helped prepare you for your future?

I really don’t know what my career dream is! Although becoming a professor seems like a likely path, there’s a not insignificant chance that I go teach high school to get the next generation interested in science, work at a nonprofit, or just find some computer science job that pays enough and has flexible enough hours that I can go back to school to focus on music or art. But just because I don’t know my plans doesn’t mean that I don’t know how the program will help – I’ll gain a rock-solid work ethic, a better understanding of the work I most enjoy doing, and a ridiculous amount of raw math and coding skills – not to mention mentorship and organizational experience.

Why do you think Theoretical and Computational Chemistry is an important and valuable field to study?

Science consists of two halves: theory and experiment. Without one half, the other is meaningless – all the raw data in the world only tells you what is happening, never why, and even the most profound ideas about the nature of things are useless without data to back them up. Computers are perhaps the most powerful tool that theory has ever had. To produce incredible science, I think that learning to integrate computation into theory is vital.

Is there anything else you’d like to add? Any advice or wisdom you would pass along to a prospective student?

Nobody knows what they’re doing, everyone is scared all the time, and if somebody seems honestly confident it’s either because they’ve gotten so good at pretending to be confident that they’ve even convinced themselves, or they got bitten by a radioactive self-help author.

Download our Guide to Theoretical and Computational Chemistry at SMU

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Earn your doctorate in chemistry at smu.

Our goal is to train the next generation of theoretical and computational chemists, who will substantially contribute to solving the current and future problems of our society by using modeling and computation. In our program you will learn how to:

Perform independent methodological research, publish your results in top-tier journals, and present your research at national and international conferences.

Engage in successful collaborations in all fields of chemistry and across disciplines stretching from materials science, nanotechnology, medicinal and pharmaceutical science, to computer science and astrophysics.

Successfully compete for highly-sought research, teaching, and consulting positions at academic institutions, federal and state agencies, and leading industry firms.

If a degree in Theoretical and Computational Chemistry is in your future, SMU will help you take your potential to the next level. Contact us to learn more, or start an application today. 

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• Theoretical and Computational Chemistry

The Department of Chemistry and Biochemistry at the University of Maryland has exceptional strength in theoretical and computational chemistry, with research focusing on the development of novel methods and computational algorithms, and the large-scale computer modeling of systems of key importance to chemistry and biology.

The faculty members with interests in theoretical  chemistry (Alexander, Fushman, Gutierrez, Jarzynski, Papoian, Salawitch, Tiwary, Vedernikov and Weeks) are international leaders in their subdisciplines. Their contributions to science have been recognized by major professional awards, including a John Simon  Guggenheim Memorial Fellowship, the  Joel Hildebrand Prize  of the American Chemical Society, and the  Raymond and Beverly Sackler Prize in Chemistry ; and the  Dudley Herschbach Prize  in the Dynamics of Molecular Collisions. John Weeks  is a member of the National Academy of Sciences and John Weeks and Chris Jarzynski are fellows of the American Academy of Arts and Sciences.

The University of Maryland provides an environment for discovery and innovation in the chemical sciences. Experimental and computational chemistry are interlinked in unique ways that often provide basic insights that are not revealed by experiment or theory alone. Research groups are integrated with other departments or institutes, including the  Institute for Physical Science and Technology (IPST) , to provide broad exposure to the challenging problem that confronts science and society today.   Theoretical Chemistry Faculty brochure

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Computational chemists aim to use computer simulations of chemical systems to understand their physical properties. The insights gained from computational chemistry can be used to interpret experimental results, guide future experiments and even design molecules and functional materials with desired chemical properties. Computational chemistry is used to tackle challenging problems in all areas of chemistry, from predicting the efficacy of pharmaceutical compounds to designing next-generation solar cells.

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• Published: 08 March 2022

Computational chemistry for all

• Kaitlin McCardle 1 &
• Jie Pan 1  

Nature Computational Science volume  2 ,  pages 134–136 ( 2022 ) Cite this article

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Dr Laura Gagliardi, professor at the University of Chicago and director of the Chicago Center for Theoretical Chemistry, shares with Nature Computational Science her research trajectory and projects, insights into the synergy between experimental and computational chemistry, and her advice for women and young scientists.

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Theory and Computation

Theoretical and computational chemistry plays a central role in research in the chemical sciences by allowing researchers to connect the fundamental physical ideas to experimental observables through classical and quantum mechanical approaches.  Theoretical chemistry aims to develop theories and models of molecular systems that provide accurate and reliable guidance for computational studies and for the analysis of experiments. New theory developments combine innovations in physical chemistry theory with advances in computer software/algorithms and mathematical models.  A common thread in all of the work in theoretical and computational chemistry at UW is connecting theoretical and computational predictions to experimental measurements.

Research Strengths

• Electronic Structure ( Dunning , Li , Xantheas ) 
• Spectroscopy and Dynamics ( Khalil , Li , Masiello , McCoy , Xantheas )
• Scientific Software ( Dunning , Li , Xantheas )
• Molecular and Materials Modeling ( Li , Masiello , McCoy , Pfaendtner , Xantheas )

Highlighted Resources

• Hyak Shared Scalable Computer Cluster 
• Center for Scalable Predictive Methods for Excitations and Correlated Phenomena
• Data Intensive Research Enabling Clean Technologies (DIRECT)
• eScience Institute
• Research Computing Club

Related Faculty

Thom H. Dunning, Jr.

Munira Khalil

Xiaosong Li

Lutz Maibaum

David J. Masiello

Anne B. McCoy

Stefan Stoll

Emeritus, adjunct, and affiliate faculty in this area, latest news.

• Prizes for Best PhD Thesis 2023 (May 3, 2024)
• First-ever atomic freeze-frame of liquid water (February 16, 2024)
• MEM-C: Moonshots & Island Voyages (July 5, 2023)
• Anne McCoy receives Jack Simons Award for Theoretical Chemistry (February 15, 2023)
• Lewis Johnson named to 40 Under 40 by Puget Sound Business Journal (September 16, 2022)
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Theoretical Chemistry

Theoretical chemistry extends our ability to study chemical systems by examining the fundamental origins of reactivity, electronic behavior, and complex organization. By developing and applying novel computational and analytical techniques, we push the frontiers of statistical mechanics, electronic structure, chemical dynamics, and emergent properties in chemistry, materials science, and biophysics.

Students, postdocs, and faculty collaborate to explore new ways of uncovering the basic principles that govern the behavior of complex chemical, material, and biophysical systems. Theoretical tools emerging from our research groups provide a foundation for the next generation of chemists to tackle both core and interdisciplinary problems in the physical, biological, and materials sciences. The University of Chicago provides a rich and interactive environment for ideas to be shared across disciplines.

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MSc in Theoretical and Computational Chemistry

• Entry requirements
• Funding and Costs

College preference

• How to apply

About the course

The three primary activities in theoretical and computational chemistry are development of new theory, implementation of methods as reliable software, and application of such methods to a host of challenges in chemical and related sciences. The MSc aims to train new research students to be able to deliver these outcomes.

The MSc consists of a set of training modules and a short project. The compulsory core modules are:

• Mathematics
• Quantum Mechanics
• Statistical Mechanics
• Introduction to Programming
• Methods of computer simulation
• Electronic structure theory
• Software Development.

You will also select a number of optional courses (currently five), which may include:

• Applied Computational Chemistry
• Biomolecular Simulation
• Mathematics II
• Quantum Mechanics in Condensed Phases
• Intermolecular Potentials
• Chemical Informatics
• Reaction Dynamics
• Advanced Quantum Mechanics
• Advanced Statistical Mechanics.

Each module consists of several lectures/classes and a piece of assessed coursework.

In addition, you will also be required to undertake one short project with an allocated supervisor. This typically takes a few weeks in either the Easter or Summer vacations. A list of possible supervisors and projects will be provided to select a topic from.

Supervision

The allocation of graduate supervision for this course is the responsibility of the Department of Chemistry and it is not always possible to accommodate the preferences of incoming graduate students to work with a particular member of staff. Under exceptional circumstances a supervisor may be found outside the Department of Chemistry.

Assessments are spread out over the academic year. 

Each module is assessed by a piece of coursework or a test.

The assessment of the short project will be based on a report that you will submit.

Graduate destinations

The number of students on this course is so small that statistics are not meaningful. Many students go on to further academic study, while others use the skills they have gained in a wide variety of destinations. The department runs a number of activities in close cooperation with the Careers Service, including an annual careers conference, CV workshops and visits from many employers. The course also has strong engagement with industrial partners.

Changes to this course and your supervision

The University will seek to deliver this course in accordance with the description set out in this course page. However, there may be situations in which it is desirable or necessary for the University to make changes in course provision, either before or after registration. The safety of students, staff and visitors is paramount and major changes to delivery or services may have to be made in circumstances of a pandemic, epidemic or local health emergency. In addition, in certain circumstances, for example due to visa difficulties or because the health needs of students cannot be met, it may be necessary to make adjustments to course requirements for international study.

Where possible your academic supervisor will not change for the duration of your course. However, it may be necessary to assign a new academic supervisor during the course of study or before registration for reasons which might include illness, sabbatical leave, parental leave or change in employment.

For further information please see our page on changes to courses and the provisions of the student contract regarding changes to courses.

Entry requirements for entry in 2024-25

Proven and potential academic excellence.

The requirements described below are specific to this course and apply only in the year of entry that is shown. You can use our interactive tool to help you  evaluate whether your application is likely to be competitive .

Please be aware that any studentships that are linked to this course may have different or additional requirements and you should read any studentship information carefully before applying. 

Degree-level qualifications

As a minimum, applicants should hold or be predicted to achieve the following UK qualifications or their equivalent:

• a first-class or strong upper second-class undergraduate degree with honours in chemistry, physics, materials science or a related discipline, with appropriate background in mathematics, quantum mechanics and statistical mechanics.

However, entrance is very competitive and most successful applicants have a first-class degree or the equivalent.

If your degree is not from the UK or another country specified above, visit our International Qualifications page for guidance on the qualifications and grades that would usually be considered to meet the University’s minimum entry requirements.

GRE General Test scores

No Graduate Record Examination (GRE) or GMAT scores are sought.

Other qualifications, evidence of excellence and relevant experience

• Applicants with substantial professional experience are welcome.
• Prior publications are not expected.

English language proficiency

This course requires proficiency in English at the University's  higher level . If your first language is not English, you may need to provide evidence that you meet this requirement. The minimum scores required to meet the University's higher level are detailed in the table below.

*Previously known as the Cambridge Certificate of Advanced English or Cambridge English: Advanced (CAE) † Previously known as the Cambridge Certificate of Proficiency in English or Cambridge English: Proficiency (CPE)

Your test must have been taken no more than two years before the start date of your course. Our Application Guide provides  further information about the English language test requirement .

Declaring extenuating circumstances

If your ability to meet the entry requirements has been affected by the COVID-19 pandemic (eg you were awarded an unclassified/ungraded degree) or any other exceptional personal circumstance (eg other illness or bereavement), please refer to the guidance on extenuating circumstances in the Application Guide for information about how to declare this so that your application can be considered appropriately.

You will need to register three referees who can give an informed view of your academic ability and suitability for the course. The  How to apply  section of this page provides details of the types of reference that are required in support of your application for this course and how these will be assessed.

Supporting documents

You will be required to supply supporting documents with your application. The  How to apply  section of this page provides details of the supporting documents that are required as part of your application for this course and how these will be assessed.

Performance at interview

Interviews are normally held as part of the admissions process. The criteria for shortlisting are academic merit, references and motivation. Those who are shortlisted will be invited to attend interview, which will typically last around 30 minutes. There will be at least two interviewers.

How your application is assessed

Your application will be assessed purely on your proven and potential academic excellence and other entry requirements described under that heading.

References  and  supporting documents  submitted as part of your application, and your performance at interview (if interviews are held) will be considered as part of the assessment process. Whether or not you have secured funding will not be taken into consideration when your application is assessed.

An overview of the shortlisting and selection process is provided below. Our ' After you apply ' pages provide  more information about how applications are assessed . 

Shortlisting and selection

Students are considered for shortlisting and selected for admission without regard to age, disability, gender reassignment, marital or civil partnership status, pregnancy and maternity, race (including colour, nationality and ethnic or national origins), religion or belief (including lack of belief), sex, sexual orientation, as well as other relevant circumstances including parental or caring responsibilities or social background. However, please note the following:

• socio-economic information may be taken into account in the selection of applicants and award of scholarships for courses that are part of  the University’s pilot selection procedure  and for  scholarships aimed at under-represented groups ;
• country of ordinary residence may be taken into account in the awarding of certain scholarships; and
• protected characteristics may be taken into account during shortlisting for interview or the award of scholarships where the University has approved a positive action case under the Equality Act 2010.

Processing your data for shortlisting and selection

Information about  processing special category data for the purposes of positive action  and  using your data to assess your eligibility for funding , can be found in our Postgraduate Applicant Privacy Policy.

Admissions panels and assessors

All recommendations to admit a student involve the judgement of at least two members of the academic staff with relevant experience and expertise, and must also be approved by the Director of Graduate Studies or Admissions Committee (or equivalent within the department).

Admissions panels or committees will always include at least one member of academic staff who has undertaken appropriate training.

Other factors governing whether places can be offered

The following factors will also govern whether candidates can be offered places:

• the ability of the University to provide the appropriate supervision for your studies, as outlined under the 'Supervision' heading in the  About  section of this page;
• the ability of the University to provide appropriate support for your studies (eg through the provision of facilities, resources, teaching and/or research opportunities); and
• minimum and maximum limits to the numbers of students who may be admitted to the University's taught and research programmes.

Offer conditions for successful applications

If you receive an offer of a place at Oxford, your offer will outline any conditions that you need to satisfy and any actions you need to take, together with any associated deadlines. These may include academic conditions, such as achieving a specific final grade in your current degree course. These conditions will usually depend on your individual academic circumstances and may vary between applicants. Our ' After you apply ' pages provide more information about offers and conditions . 

In addition to any academic conditions which are set, you will also be required to meet the following requirements:

Financial Declaration

If you are offered a place, you will be required to complete a  Financial Declaration  in order to meet your financial condition of admission.

Disclosure of criminal convictions

In accordance with the University’s obligations towards students and staff, we will ask you to declare any  relevant, unspent criminal convictions  before you can take up a place at Oxford.

All students will be allocated their own desk, with a computer. Access to the departmental IT network is open at all times and extensive software is available. Departmental computers, software licences and the network are supported by the department's IT staff. Network access is offered at all times via the VPN.

Internet access to all relevant recent journals is available. Books and older journal issues are available in the university science library, located within five minutes' walking distance.

In the event of difficulty, pastoral care can be offered by your college, by the project supervisor, the course leadership team and/or the director of studies.

Oxford is one of the leading chemistry research departments in the world, with around 80 academic staff carrying out international level research and an annual research income of around £15 million.

In the most recent national assessment of research (REF 2021) 66% of our research output was judged world-leading, and 32% was judged internationally excellent. The department has a number of research themes, including:

• chemistry at the interface with biology and medicine
• sustainable energy chemistry
• kinetics, dynamics and mechanism
• advanced functional materials and interfaces
• innovative measurement and photon science
• theory and modelling of complex systems.

The facilities at Oxford for research and teaching are among the best available in the UK, with a wide range of the latest instrumentation and a huge computational resource networked throughout the University and beyond to national computing centres. Among the facilities available are the latest in automated X-ray diffractometers, electron microscopes, scanning tunnelling microscopes, mass spectrometers, high-field nuclear magnetic resonance (NMR) spectrometers and specialised instruments for the study of solids.

For 2024 entry and beyond, the Department of Chemistry will offer the DPhil in Chemistry and MSc by Research in Chemistry courses, which amalgamate the previous research degrees offered in Chemical Biology, Inorganic Chemistry, Organic Chemistry, and Physical & Theoretical Chemistry.

View all courses   View taught courses View research courses

The University expects to be able to offer over 1,000 full or partial graduate scholarships across the collegiate University in 2024-25. You will be automatically considered for the majority of Oxford scholarships , if you fulfil the eligibility criteria and submit your graduate application by the relevant December or January deadline. Most scholarships are awarded on the basis of academic merit and/or potential. 

For further details about searching for funding as a graduate student visit our dedicated Funding pages, which contain information about how to apply for Oxford scholarships requiring an additional application, details of external funding, loan schemes and other funding sources.

Please ensure that you visit individual college websites for details of any college-specific funding opportunities using the links provided on our college pages or below:

Please note that not all the colleges listed above may accept students on this course. For details of those which do, please refer to the College preference section of this page.

Annual fees for entry in 2024-25

Further details about fee status eligibility can be found on the fee status webpage.

Information about course fees

Course fees are payable each year, for the duration of your fee liability (your fee liability is the length of time for which you are required to pay course fees). For courses lasting longer than one year, please be aware that fees will usually increase annually. For details, please see our guidance on changes to fees and charges .

Course fees cover your teaching as well as other academic services and facilities provided to support your studies. Unless specified in the additional information section below, course fees do not cover your accommodation, residential costs or other living costs. They also don’t cover any additional costs and charges that are outlined in the additional information below.

Where can I find further information about fees?

The Fees and Funding  section of this website provides further information about course fees , including information about fee status and eligibility  and your length of fee liability .

Additional information

There are no compulsory elements of this course that entail additional costs beyond fees and living costs. However, as part of your course requirements, you may need to choose a dissertation, a project or a thesis topic. Please note that, depending on your choice of topic and the research required to complete it, you may incur additional expenses, such as travel expenses, research expenses, and field trips. You will need to meet these additional costs, although you may be able to apply for small grants from your department and/or college to help you cover some of these expenses.

Living costs

In addition to your course fees, you will need to ensure that you have adequate funds to support your living costs for the duration of your course.

For the 2024-25 academic year, the range of likely living costs for full-time study is between c. £1,345 and £1,955 for each month spent in Oxford. Full information, including a breakdown of likely living costs in Oxford for items such as food, accommodation and study costs, is available on our living costs page. The current economic climate and high national rate of inflation make it very hard to estimate potential changes to the cost of living over the next few years. When planning your finances for any future years of study in Oxford beyond 2024-25, it is suggested that you allow for potential increases in living expenses of around 5% each year – although this rate may vary depending on the national economic situation. UK inflationary increases will be kept under review and this page updated.

Students enrolled on this course will belong to both a department/faculty and a college. Please note that ‘college’ and ‘colleges’ refers to all 43 of the University’s colleges, including those designated as societies and permanent private halls (PPHs). 

If you apply for a place on this course you will have the option to express a preference for one of the colleges listed below, or you can ask us to find a college for you. Before deciding, we suggest that you read our brief  introduction to the college system at Oxford  and our  advice about expressing a college preference . For some courses, the department may have provided some additional advice below to help you decide.

The following colleges accept students on the MSc in Theoretical and Computational Chemistry:

• Balliol College
• Brasenose College
• Christ Church
• Corpus Christi College
• Exeter College
• Jesus College
• Lady Margaret Hall
• Linacre College
• Lincoln College
• Merton College
• New College
• Oriel College
• Pembroke College
• The Queen's College
• Reuben College
• St Anne's College
• St Catherine's College
• St Cross College
• St Edmund Hall
• St Hilda's College
• St John's College
• University College
• Wadham College
• Wolfson College
• Wycliffe Hall

Before you apply

Our  guide to getting started  provides general advice on how to prepare for and start your application. You can use our interactive tool to help you  evaluate whether your application is likely to be competitive .

If it's important for you to have your application considered under a particular deadline – eg under a December or January deadline in order to be considered for Oxford scholarships – we recommend that you aim to complete and submit your application at least two weeks in advance . Check the deadlines on this page and the  information about deadlines and when to apply  in our Application Guide.

Application fee waivers

An application fee of £75 is payable per course application. Application fee waivers are available for the following applicants who meet the eligibility criteria:

• applicants from low-income countries;
• refugees and displaced persons; 
• UK applicants from low-income backgrounds; and 
• applicants who applied for our Graduate Access Programmes in the past two years and met the eligibility criteria.

You are encouraged to  check whether you're eligible for an application fee waiver  before you apply.

Do I need to contact anyone before I apply?

Prior to applying, you are encouraged to communicate with the department in order to refine your application. Informal enquiries should be made to the department's Graduate Studies Administrator in the first instance, via the contact details provided on this page.

Completing your application

You should refer to the information below when completing the application form, paying attention to the specific requirements for the supporting documents .

For this course, the application form will include questions that collect information that would usually be included in a CV/résumé. You should not upload a separate document. If a separate CV/résumé is uploaded, it will be removed from your application .

If any document does not meet the specification, including the stipulated word count, your application may be considered incomplete and not assessed by the academic department. Expand each section to show further details.

Referees: Three overall, academic preferred

Whilst you must register three referees, the department may start the assessment of your application if two of the three references are submitted by the course deadline and your application is otherwise complete. Please note that you may still be required to ensure your third referee supplies a reference for consideration.

References should generally be academic though a maximum of one professional reference is acceptable where you have completed an industrial placement or worked in a full-time position.

Your references will support intellectual ability, academic achievement, motivation, and ability to work in a group.

Official transcript(s)

Your transcripts should give detailed information of the individual grades received in your university-level qualifications to date. You should only upload official documents issued by your institution and any transcript not in English should be accompanied by a certified translation.

More information about the transcript requirement is available in the Application Guide.

Statement of purpose/personal statement: A minimum of 1,000 words to a maximum of 1,500 words

Your statement should be written in English and explain your motivation for applying for the course at Oxford, your relevant experience and education, and the specific areas that interest you and/or you intend to specialise in.

If possible, please ensure that the word count is clearly displayed on the document.

This will be assessed for the coherence of the statement; evidence of motivation for and understanding of the proposed area of study; the ability to present a reasoned case in English; and commitment to the subject.

Start or continue your application

You can start or return to an application using the relevant link below. As you complete the form, please  refer to the requirements above  and  consult our Application Guide for advice . You'll find the answers to most common queries in our FAQs.

Application Guide   Apply

ADMISSION STATUS

Open - applications are still being accepted

Up to a week's notice of closure will be provided on this page - no other notification will be given

12:00 midday UK time on:

Friday 10 November 2023 Applications more likely to receive earlier decisions

Friday 19 January 2024 Latest deadline for most Oxford scholarships

Friday 1 March 2024 Applications may remain open after this deadline if places are still available - see below

A later deadline shown under 'Admission status' If places are still available,  applications may be accepted after 1 March . The 'Admissions status' (above) will provide notice of any later deadline.

*Three-year average (applications for entry in 2021-22 to 2023-24)

Further information and enquiries

This course is offered by the Department of Chemistry

• The department's website
• Staff and Theoretical Chemistry Group  in the Dept. of Chemistry
• Mathematical, Physical and Life Sciences
• Residence requirements for full-time courses
• Postgraduate applicant privacy policy

Course-related enquiries

Advice about contacting the department can be found in the How to apply section of this page

✉  [email protected] ☎ +44 (0)1865 272569

Application-process enquiries

See the application guide

Other courses to consider

You may also wish to consider applying to other courses that are similar or related to this course:

View related courses

100 Best colleges for Computational Chemistry in the United States

Updated: February 29, 2024

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Below is a list of best universities in the United States ranked based on their research performance in Computational Chemistry. A graph of 10.9M citations received by 252K academic papers made by 330 universities in the United States was used to calculate publications' ratings, which then were adjusted for release dates and added to final scores.

We don't distinguish between undergraduate and graduate programs nor do we adjust for current majors offered. You can find information about granted degrees on a university page but always double-check with the university website.

1. University of California - Berkeley

For Computational Chemistry

2. University of Minnesota - Twin Cities

3. University of Illinois at Urbana - Champaign

4. Stanford University

5. Massachusetts Institute of Technology

6. Princeton University

7. Cornell University

8. California Institute of Technology

9. Harvard University

10. University of Wisconsin - Madison

11. Northwestern University

12. Pennsylvania State University

13. University of North Carolina at Chapel Hill

14. Columbia University

15. University of Florida

16. University of California-San Diego

17. Carnegie Mellon University

18. Georgia Institute of Technology

19. University of California - Los Angeles

20. Yale University

21. University of Texas at Austin

22. University of Washington - Seattle

23. Iowa State University

24. University of Michigan - Ann Arbor

25. Purdue University

26. University of Utah

27. University of Pennsylvania

28. Rice University

29. University of California - Santa Barbara

30. Rutgers University - New Brunswick

31. Tulane University of Louisiana

32. University of Chicago

33. University of Southern California

34. Texas A&M University - College Station

35. University of Georgia

36. Ohio State University

37. University of California - Irvine

38. Johns Hopkins University

39. University of California - San Francisco

40. University of California - Davis

41. University of Maryland - College Park

42. Duke University

43. Boston University

44. University of Pittsburgh

45. New York University

46. Michigan State University

47. University of Tennessee - Knoxville

48. University of Delaware

49. North Carolina State University at Raleigh

50. University of Arizona

51. University of Colorado Boulder

52. Stony Brook University

53. Emory University

54. University of Notre Dame

55. Arizona State University - Tempe

56. University at Buffalo

57. University of Virginia

58. University of Rochester

59. Washington State University

60. Virginia Polytechnic Institute and State University

61. University of Maryland, Baltimore

62. University of Houston

63. University of New Orleans

64. University of California - Riverside

65. University of Illinois at Chicago

66. Vanderbilt University

67. Wayne State University

68. Rensselaer Polytechnic Institute

69. Florida State University

70. University of Kansas

71. Brown University

72. University of Missouri - Columbia

73. Providence College

74. Washington University in St Louis

75. University of Nebraska - Lincoln

76. University of Massachusetts - Amherst

77. Louisiana State University and Agricultural & Mechanical College

78. Virginia Commonwealth University

79. Colorado State University - Fort Collins

80. University of North Texas

81. Jackson State University

82. University of Central Florida

83. Case Western Reserve University

84. Temple University

85. University of Iowa

86. University of Kentucky

87. University of Arkansas

88. University of New Mexico

89. Texas Tech University

90. University of Connecticut

91. University of South Carolina - Columbia

92. Utah State University

93. Kansas State University

94. University of Oregon

95. Wesleyan University

96. Clemson University

97. University of Cincinnati

98. Northeastern University

99. Drexel University

100. Georgetown University

The best cities to study Computational Chemistry in the United States based on the number of universities and their ranks are Berkeley , Minneapolis , Champaign , and Stanford .

Chemistry subfields in the United States

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Research Tracks

• Theoretical and Computational Chemistry

This track emphasizes the development of new theoretical methods and simulation approaches for application to current chemistry and biochemistry problems. Over the past decade, theoretical chemistry and computational chemistry have undergone a revolution triggered by the advent of new theories/algorithms and high-performance supercomputers, making possible the study of increasingly large and complex systems. Current research at UCSD covers a broad range of topics that include quantum-mechanical methodologies for energy and electron transport, non-equilibrium statistical mechanics, theoretical and computational approaches for biomolecular simulations, drug discovery, protein-protein interaction networks, carbon capture and hydrogen storage in porous materials, theoretical geochemistry, computational modeling of heterogeneous chemistry relevant to climate and the environment, electronic structure calculations of organic, inorganic and organometallic complexes, and magnetic and transport properties of metal-organic frameworks.

• Analytical and Atmospheric Chemistry
• Chemical Biology
• Inorganic Chemistry
• Materials Chemistry
• Organic Chemistry
• Physical Chemistry

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Course closed:

Chemistry is no longer accepting new applications.

The PhD is offered by the Department of Chemistry as a full or part-time period of research and introduces students to research skills and specialist knowledge. 

Please note: part-time study may not always be viable and will be considered on a case-by-case basis, so please discuss this option with your proposed supervisor before making an application for this mode of study. There are attendance requirements and part-time students will need to live close enough to Cambridge to fulfil these.

Students are integrated into the research culture of the Department by joining a research group, supervised by one of our academic staff,  in one of the following areas of chemistry:

Biological Chemistry

Life is the chemistry that goes on inside every one of us. We seek to understand this chemistry, both the physical processes occurring at the molecular level and the chemical reactions, and we also seek to control the chemistry as a way to treat diseases. Biological Chemistry at Cambridge comprises several research groups with additional contributions from many more. The major themes are biological polymers, proteins and nucleic acids - how they interact with each other and with small molecules. How do proteins fold to a defined structure and why do they sometimes not fold properly but aggregate causing neurodegenerative diseases? How do proteins catalyse the reactions that they do and can we make small molecules that inhibit these processes? What structures can nucleic acids adopt? How can we detect and what is the role of modifications of individual nucleotides? How can we target medicinally active compounds to where they are needed in the body? By addressing these questions, we seek to improve human health and the treatment of diseases.

Materials Chemistry

The technological devices we depend on, from aeroplanes to mobile phones, rely upon ever-increasing structural complexity for their function. Designing complex materials for these devices through the art of chemical synthesis brings challenges and opportunities.

Members of the Materials RIG invent new materials in view of potential applications. Modern materials chemistry is a wide ranging topic and includes surfaces, interfaces, polymers, nanoparticles and nanoporous materials, self assembly, and biomaterials, with applications relevant to oil recovery and separation, catalysis, photovoltaics, fuel cells and batteries, crystallisation and pharmaceutical formulation, gas sorption, energy, functional materials, biocompatible materials, computer memory, and sensors. 

Physical and Atmospheric Chemistry

Physical Chemistry at Cambridge has two broad but overlapping aims. One is to understand the properties of molecular systems in terms of physical principles. This work underpins many developing technological applications that affect us all, such as nanotechnology, sensors and molecular medicine. The other is atmospheric chemistry where the interactions between chemical composition, climate and health are studied using a range of computer modelling and experiment-based approaches. Together these two areas form a richly interdisciplinary subject spanning the full range of scientific methodologies: experimental, theoretical and computational. It is a research area with something for everyone.

Synthetic Chemistry

Synthetic research at the University of Cambridge is focused on the development of innovative new methods to make and use molecules of function. Our interests range from the innovative catalytic strategies to make small molecules, to supramolecular assemblies or the total synthesis of biologically important compounds and natural products. Our research is diverse, pioneering and internationally leading. The dynamic environment created by the research groups working at the cutting edge of the field, makes postgraduate research at Cambridge the best place for outstanding and motivated students.

Theoretical Chemistry

Research in Theoretical Chemistry covers a wide range of lengths and timescales, including the active development of new theoretical and computational tools. The applications include high-resolution spectroscopy, atomic and molecular clusters, biophysics, surface science, and condensed matter, complementing experimental research in the Department.

We develop new tools for quantum and classical simulations, informatics, and investigate molecules using descriptions that range from atomic detail to coarse-grained models of mesoscopic matter. This work often begins with analytical theory, which is developed into new computer programs, applied to molecules and materials of contemporary interest, and ultimately compared with experiment.

Educational aims of the PhD programme:

• give students with relevant experience at the master's level the opportunity to carry out focused research in the discipline under close supervision;
• give students the opportunity to acquire or develop skills and expertise relevant to their research interests;
• provide all students with relevant and useful researcher development training opportunities to broaden their horizons and properly equip them for the opportunity which they seek following their PhD studies.

Learning Outcomes

By the end of the programme, students will have

• a comprehensive understanding of techniques, and a thorough knowledge of the literature, applicable to their own research;
• demonstrated originality in the application of knowledge, together with a practical understanding of how research and enquiry are used to create and interpret knowledge in their field;
• shown abilities in the critical evaluation of current research, research techniques and methodologies;
• demonstrated some self-direction and originality in tackling and solving problems, and acted autonomously in the planning and implementation of research; and
• taken up relevant and highly useful researcher development training opportunities to develop skills and attributes for their desired future career.

Students currently studying for a relevant Master's degree at the University of Cambridge will normally need to obtain a pass in order to be eligible to continue onto the PhD in Chemistry.

The Postgraduate Virtual Open Day usually takes place at the end of October. It’s a great opportunity to ask questions to admissions staff and academics, explore the Colleges virtually, and to find out more about courses, the application process and funding opportunities. Visit the  Postgraduate Open Day  page for more details.

See further the  Postgraduate Admissions Events  pages for other events relating to Postgraduate study, including study fairs, visits and international events.

The Department of Chemistry hosts a virtual open day for prospective postgraduate students comprising online laboratory tours, a chance to meet with current students and academic staff, and an opportunity to talk to professional services staff about the application process. 

Key Information

3-4 years full-time, 4-7 years part-time, study mode : research, doctor of philosophy, department of chemistry, course - related enquiries, application - related enquiries, course on department website, dates and deadlines:, lent 2024 (closed).

Some courses can close early. See the Deadlines page for guidance on when to apply.

Easter 2024 (Closed)

Michaelmas 2024 (closed), lent 2025 (closed), easter 2025 (closed), funding deadlines.

These deadlines apply to applications for courses starting in Michaelmas 2024, Lent 2025 and Easter 2025.

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PhD program of AI for Chemistry

24 May 2024 Job Information Organisation/Company Lappeenranta – Lahti University of Technology LUT Research Field Computer science » Modelling tools Chemistry » Reaction mechanisms and dynamics

PhD student in Materials Chemistry at the Program for Inorganic Chemistry

Published: 2024-05-29 The Department of Chemistry - Ångström conducts research and education in the chemistry field. The department has more than 270 employees and has a turnover of 290 million SEK

PhD Position in Computer Science / Computational Chemistry

Alliance for Computational Systems Chemistry ) Marie-Skłodowska-Curie Joint Doctoral Network. This network consists of fifteen (15) highly interlinked PhD projects, of which this particular call is for a

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at the Ångström Advanced Battery Centre (ÅABC – https://kemi.uu.se/angstrom/research/structural- chemistry /aabc ), which are both parts of the Structural Chemistry program at Uppsala University. The PhD project

PhD Studentship: Computational Chemistry Driven Design of Improved Thermal Batteries

4-year Computational Project to use state-of-the-art Computational Chemistry techniques to understand structure-property relationships in thermal batteries, and to derive new understanding to guide

Two PhD positions in Computational Biophysics/- chemistry

a Research Infrastructure? No Offer Description Two PhD positions on Computational Biophysics/ chemistry and on the Dynamics of Open Quantum Systems are available in the group of Prof. Ulrich

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a Research Infrastructure? No Offer Description MARIE SKŁODOWSKA-CURIE DN PhD Position in Computational Chemistry to work on “Theoretical Approaches to Model Solvent Effects on (Time-resolved

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Professor in Computational Chemistry , Chemistry Department) Start Date: As soon as possible, by 1st September 2024 at latest Applications are invited for a 3-year funded PhD studentship, sponsored by

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: •    Perform research in the computational chemistry theme of the van 't Hoff Institute for Molecular Sciences; •    Be an active member of the computational chemistry theme; •    Take part actively in

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Illinois chemistry team wins computational science hackathon

A team from the Department of Chemistry took first place among 12 teams in a cross-campus computational science competition at the National Center for Supercomputing Applications .

Three graduate students, Jason Wu, Shruti Iyer, and Seonghwan Kim, and postdoctoral researcher Zheng Yu won the Ashby Prize in Computational Science Hackathon on April 23.

“This is a cross-campus hackathon sponsored by the NCSA,” said Prof. Nick Jackson, who encouraged the four members of his research group to enter the contest. Wu and Kim are co-advised by Prof. Charles Schroeder in Materials Science and Engineering.

“Remarkably, they managed to win first place despite not having any computer scientists on their team,” Jackson said.

The competition is co-organized by the  Center for Artificial Intelligence Innovation  at the NCSA on the University of Illinois Urbana-Champaign campus. The main goal of the hackathon is to let talented U. of I. students showcase their skills in a friendly competition while working on challenging problems involving computational science and machine learning using state-of-the-art computational systems at NCSA.

The competition takes place at the NCSA over a 48-hour period as teams utilize the state-of-the-art systems to execute their project and then present their final work two days later during the NCSA Student Research Conference.

Hackathon teams were challenged to build a front-end workflow management system using Large Language Models (LLMs) and related tools to setup and execute computational workflows. Students were provided with access to the Delta supercomputer and provided LLM access/credits.

The competition began with more than 50 participants across 12 teams. Each team was required to have at least one student from the Computer Science Department, but the chemistry team petitioned the organizers for an exception to this rule, which was granted.

Nine of the 12 teams successfully completed the hackathon and presented their results.

The chemistry team created a system called “Mol-Hunter: an artificial intelligence agent for automated molecular discovery and synthesis.” Their workflow included machine learning predictions, molecular dynamics simulations, quantum mechanical calculations, literature search, a database application programming interface, and a retrosynthetic reaction network search.

Seonghwan Kim, a third-year materials science and engineering graduate student in the Jackson and Schroeder groups, said the team was motivated to be in the competition because they all wanted experience utilizing LLMs for automated molecular discovery in their research.  Large Language Models, like GPT4, Kim explained, are having huge impacts in chemistry, so many researchers are trying to use LLMs for automated lab work.

“That’s what motivated us, and we enjoyed learning lots of large language models during the Hackathon and communicating with a lot of computer science students and professors,” he said.

Iyer, a second-year chemistry graduate student in the Jackson group, said the overall goal was coming up with a computational workflow that could predict the physical properties of a particular molecule and then generate a synthesis pathway for that molecule.

In the Jackson Lab, Kim said the team has gained experience using machine learning in chemistry research, so they could seamlessly transfer those skills to this project, combining machine learning predictions and molecular simulations with LLMs to try to build an autonomous workflow.

One of the challenges they had to overcome, said Wu, a first-year chemistry graduate student in the Jackson and Schroeder labs, was not being very familiar with LLMs. So, the competition was a bit of a LLM crash course for the team members, who learned a lot in just two days with technical support from NCSA staff.

Yu said it was just a really great learning environment for them.

“This is an area that we don't have high expertise in, but the fact that we were all working on it together and then the environment of only having 48 to 72 hours to complete a huge project like this, all of that together really fostered that good productive sort of working environment,” Yu said. “We went in there the first day knowing nothing about how to program the language models, but by the end, not only did we have this project, but we also learned all the tools that can be helpful to our future research.”

The team said that their project as well as the knowledge they gained will factor into research in their lab. In particular, the team members in the Jackson lab are interested in extending the Mol-Hunter workflow to their work on the Open Macromolecular Genome – an open polymer property database to enable generative AI in the chemical sciences.

“We think that the Mol-Hunter project could represent a new paradigm for interfacing non-expert chemical scientists with advanced machine learning architectures via chatbot-like functionality enabled by large language models,” Jackson said.

And Yu said this project could be a springboard for his career.

“I'm trying to get a job in academia, and I think this large language model can be one direction for me to work on in the following 10 years,” he said.

Kim said he really enjoyed the collaboration process with his teammates.

“This Hackathon doesn't have specific individual tasks, so we had to discuss together what to do together,” he said. “That was a fun process.”

Iyer said she also enjoyed collaborating with her teammates and the learning process.

“My part of the project was something I think a computer science student would have been able to do much quicker, because it was very heavy on data structures and algorithms. And that's not something I have studied, but being able to figure that out and implement it to the problem that was satisfying for me personally,” she said.

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Researchers apply quantum computing methods to protein structure prediction

Combining quantum and classical methods in computer simulations.

Researchers from Cleveland Clinic and IBM recently published findings in the Journal of Chemical Theory and Computation that could lay the groundwork for applying quantum computing methods to protein structure prediction. This publication is the first peer-reviewed quantum computing paper from the Cleveland Clinic-IBM Discovery Accelerator partnership.

For decades, researchers have leveraged computational approaches to predict protein structures. A protein folds itself into a structure that determines how it functions and binds to other molecules in the body. These structures determine many aspects of human health and disease.

By accurately predicting the structure of a protein, researchers can better understand how diseases spread and thus how to develop effective therapies. Cleveland Clinic postdoctoral fellow Bryan Raubenolt, Ph.D., and IBM researcher Hakan Doga, Ph.D., spearheaded a team to discover how quantum computing can improve current methods.

In recent years, machine learning techniques have made significant progress in protein structure prediction. These methods are reliant on training data (a database of experimentally determined protein structures) to make predictions. This means that they are constrained by how many proteins they have been taught to recognize. This can lead to lower levels of accuracy when the programs/algorithms encounter a protein that is mutated or very different from those on which they were trained, which is common with genetic disorders.

The alternative method is to simulate the physics of protein folding. Simulations allow researchers to look at a given protein's various possible shapes and find the most stable one. The most stable shape is critical for drug design.

The challenge is that these simulations are nearly impossible on a classical computer, beyond a certain protein size. In a way, increasing the size of the target protein is comparable to increasing the dimensions of a Rubik's cube. For a small protein with 100 amino acids, a classical computer would need the time equal to the age of the universe to exhaustively search all the possible outcomes, says Dr. Raubenolt.

To help overcome these limitations, the research team applied a mix of quantum and classical computing methods. This framework could allow quantum algorithms to address the areas that are challenging for state-of-the-art classical computing, including protein size, intrinsic disorder, mutations and the physics involved in proteins folding. The framework was validated by accurately predicting the folding of a small fragment of a Zika virus protein on a quantum computer, compared to state-of-the-art classical methods.

The quantum-classical hybrid framework's initial results outperformed both a classical physics-based method and AlphaFold2. Although the latter is designed to work best with larger proteins, it nonetheless demonstrates this framework's ability to create accurate models without directly relying on substantial training data.

The researchers used a quantum algorithm to first model the lowest energy conformation for the fragment's backbone, which is typically the most computationally demanding step of the calculation. Classical approaches were then used to convert the results obtained from the quantum computer, reconstruct the protein with its sidechains, and perform final refinement of the structure with classical molecular mechanics force fields. The project shows one of the ways that problems can be deconstructed into parts, with quantum computing methods addressing some parts and classical computing others, for increased accuracy.

"One of the most unique things about this project is the number of disciplines involved," says Dr. Raubenolt. "Our team's expertise ranges from computational biology and chemistry, structural biology, software and automation engineering, to experimental atomic and nuclear physics, mathematics, and of course quantum computing and algorithm design. It took the knowledge from each of these areas to create a computational framework that can mimic one of the most important processes for human life."

The team's combination of classical and quantum computing methods is an essential step for advancing our understanding of protein structures, and how they impact our ability to treat and prevent disease. The team plans to continue developing and optimizing quantum algorithms that can predict the structure of larger and more sophisticated proteins.

"This work is an important step forward in exploring where quantum computing capabilities could show strengths in protein structure prediction," says Dr. Doga. "Our goal is to design quantum algorithms that can find how to predict protein structures as realistically as possible."

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Story Source:

Materials provided by Cleveland Clinic . Note: Content may be edited for style and length.

Journal Reference :

• Hakan Doga, Bryan Raubenolt, Fabio Cumbo, Jayadev Joshi, Frank P. DiFilippo, Jun Qin, Daniel Blankenberg, Omar Shehab. A Perspective on Protein Structure Prediction Using Quantum Computers . Journal of Chemical Theory and Computation , 2024; 20 (9): 3359 DOI: 10.1021/acs.jctc.4c00067

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