mit computer science phd application

MIT Interdisciplinary Doctoral Program in Computational Science and Engineering

• CSE PhD Overview
• Dept-CSE PhD Overview
• CSE Doctoral Theses
• Program Overview and Curriculum
• For New CCSE Students
• Terms of Reference

MIT Interdisciplinary Doctoral Program in Computational Science and Engineering (Dept-CSE PhD)

• Dept-CSE PhD Program of Study Form   (version date 05Feb2024)
• Checklist for Dept-CSE PhD Students (version date 05Sep2023)

Dept-CSE PhD Participating Departments

The interdisciplinary doctoral program in Computational Science and Engineering ( CSE PhD + Engineering or Science ) at MIT allows enrolled students to specialize at the doctoral level in a computation-related field of their choice through focused coursework and a doctoral thesis. This program is offered through a number of participating departments, namely

• Civil and Environmental Engineering (Course 1) ,
• Mechanical Engineering (Course 2) ,
• Materials Science and Engineering (Course 3) ,
• Chemical Engineering (Course 10) ,
• Earth, Atmospheric and Planetary Sciences (Course 12) ,
• Aeronautics and Astronautics (Course 16) ,
• Mathematics (Course 18) ,
• Nuclear Science & Engineering (Course 22) .

Program Outline

Once admitted, doctoral degree candidates are expected to complete the host department’s degree requirements (including qualifying exam) with CSE deviations relating to coursework, thesis committee composition and thesis submission that are specific to the Dept-CSE program and are discussed in more detail below.

Academic Performance

Dept-CSE PhD students are required to complete at least five graduate-level subjects, totaling no less than 60 credit units, in computational science and engineering selected from the approved list of Computational Concentration Subjects . Dept-CSE PhD students may not use more than 12 units of credit from a “meets with undergraduate” subject to fulfill the CSE curriculum requirement. Subjects taken with the graduate P/D/F grading option, or subjects specifically designated as P/D/F in the MIT Bulletin, cannot be used to satisfy the Dept-CSE PhD curricular requirement of five graduate-level subjects, totaling no less than 60 credit units, in computational science and engineering*.

In addition to departmental academic performance expectations, Dept-CSE students are expected to maintain a grade point average (GPA) of at least 4.5 (out of 5) in CSE subjects and an overall GPA of at least 4.2 (out of 5) during the course of their studies.

*ChemE-CSE students are required to complete at least four subjects in computational science and engineering, in addition to 10.34, for a total of no less than 57 credit units.

Department of Civil and Environmental Engineering

A complete description of the doctoral program in Civil and Environmental Engineering can be found at https://cee.mit.edu/resources/ . Deviations associated with the CEE-CSE degree (“1.CSD”) are as follows.

Coursework Requirements

The CEE-CSE doctoral program of study consists of at least five graduate-level subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects . Subjects taken as part of an MIT SM degree can be counted toward this requirement. Doctoral candidates are normally expected to take their major subjects at the Institute. The specific subjects will depend on the student’s thesis topic and background, and will be approved by their thesis committee.

Thesis Committee Composition

The thesis committee composition requirements are identical to those of Course 1, with the additional requirement that that either the advisor be a CCSE member or the committee contain at least two CCSE members.

Thesis Submission

In addition to approval from the Chair of Course 1 Graduate Program Committee, the complete thesis needs to be submitted to and approved by CCSE. Students should provide a copy of the thesis title page to the CCSE academic administrator for review and approval prior to submitting the final thesis.

Thesis Fields

Course 1 will award degrees under the thesis fields “Civil Engineering and Computation” and “Environmental Engineering and Computation.”

Department of Mechanical Engineering

A complete description of the doctoral program in Mechanical Engineering can be found at http://meche.mit.edu/academic/graduate . Deviations associated with the CSE degree are as follows. MechE-CSE PhD candidates (“2.CSD”) are expected to pass the ME qualifying exam in Computational Engineering (present thesis in computational engineering and take computational engineering subject exam).

The MechE-CSE doctoral program of study consists of at least five graduate-level subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects . Subjects taken as part of an MIT SM degree can be counted toward this requirement. Doctoral candidates are normally expected to take their major subjects at the Institute. The specific subjects will depend on the student’s thesis topic and background, and will be approved by their thesis committee.

The thesis committee composition requirements are identical to those of Course 2, with the additional requirement that  either the advisor be a CCSE member or the committee contain at least two CCSE members.

In addition to approval from the ME Graduate Officer, the complete thesis needs to be submitted to and approved by CCSE. Students should provide a copy of the thesis title page to the CCSE academic administrator for review and approval prior to submitting the final thesis.

Thesis Field

Course 2 will award degrees under the thesis field “Mechanical Engineering and Computation.”

Department of Materials Science and Engineering

A complete description of the graduate program in the Department of Materials Science and Engineering (DMSE) can be found via https://dmse.mit.edu/graduate/programs . Deviations associated with the DMSE-CSE degree (“3.CSD”) are as follows.

The DMSE-CSE doctoral program of study consists of at least five graduate subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects . The CSE five-course requirement can be satisfied through courses that simultaneously satisfy the DMSE core, post-core electives, and/or minor requirements. CSE subjects that a student may have applied towards a MIT SM degree may also be applied towards a DMSE-CSE doctoral major field of study requirement. Doctoral candidates are normally expected to take their major subjects at the Institute. The specific subjects will depend on the student’s thesis topic and background, and will be approved by Thesis Committee.

The Thesis committee composition requirements are identical to those of DMSE, with the additional requirement that that either  the advisor be a CCSE member  or  the committee contain at least two CCSE members.

In addition to approval from the Chair of the Departmental Graduate Program Committee, the complete thesis needs to be submitted to and approved by CCSE. Students should provide a copy of the thesis title page to the CCSE academic administrator for review and approval prior to submitting the final thesis.

DMSE will award degrees under the Thesis field “Computational Materials Science and Engineering”.

Department of Chemical Engineering

A complete description of the doctoral program in Chemical Engineering can be found at  http://web.mit.edu/cheme/academics/grad/advising.html#phdscd . Deviations associated with the ChemE-CSE degree are as follows.

ChemE-CSE students (“10.CSD”) are expected to complete the ChemE core curriculum with a CSE minor consisting of at least four graduate level subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects .  The minor subjects shall not include 10.34, which is already part of the Chemical Engineering core curriculum. Subjects taken as part of an MIT SM program can be counted toward this requirement. Doctoral candidates are normally expected to take their major subjects at the Institute. The specific subjects will depend on the student’s thesis topic and background, and will be approved by the student’s thesis committee.

The thesis committee composition requirements are identical to those of Course 10, with the additional requirement that  either  the committee chair be a CCSE member  or  the committee contain at least two CCSE members.

Course 10 will award degrees under the thesis field “Chemical Engineering and Computation.”

Department of Earth, Atmospheric and Planetary Sciences

Once admitted, doctoral degree candidates are expected to complete the Course 12 degree requirements as outlined at https://eapsweb.mit.edu/academic-resources/grad-resources , except those relating to coursework in the Major Field of Study, Thesis Committee Composition and Thesis Submission that are specific to the EAPS-CSE program and are discussed in more detail below.

Degree candidates are expected to pass the qualifying exam in Course 12.

The EAPS-CSE (“12.CSD”) doctoral program of study consists of at least five graduate-level subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects . The specific subjects will depend on the student’s thesis topic and background, and will be approved by the Thesis Committee. Subjects taken as part of an MIT SM program can be counted toward this requirement. Doctoral candidates are normally expected to take their major subjects at the Institute.

The Thesis committee composition requirements are identical to those of Course 12, with the additional requirement that either the advisor be a CCSE member or the committee contain at least two CCSE members.

In addition to approval from the Examination Committee, the complete thesis needs to be submitted to and approved by CCSE. Students should provide a copy of the thesis title page to the CCSE academic administrator for review and approval prior to submitting the final thesis.

Course 12 will award degrees under the Thesis field ” Computational Earth, Atmospheric and Planetary Sciences “.

Department of Aeronautics and Astronautics

A complete description of the doctoral program in Aeronautics and Astronautics can be found at http://aeroastro.mit.edu/graduate-program/doctoral-degree . Deviations associated with the AeroAstro-CSE degree are as follows. AeroAstro-CSE PhD candidates (“16.CSD”) are expected to pass the Aerospace Computational Engineering track qualifying exam in Course 16.

The AeroAstro-CSE doctoral program of study consists of at least five graduate-level subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects . Subjects taken as part of an MIT SM program can be counted toward this requirement. Doctoral candidates are normally expected to take their major subjects at the Institute. The specific subjects will depend on the student’s thesis topic and background, and will be approved by thesis committee.

The thesis committee composition requirements are identical to those of Course 16, with the additional requirement that either the advisor be a CCSE member or the committee contain at least two CCSE members.

Course 16 will award degrees under the thesis field “Computational Science and Engineering” to students matriculating in/before September 2023 and “Aerospace Engineering and Computational Science” for students matriculating after September 2023.

Department of Mathematics

A description of the plan of study for the Applied Mathematics option of the PhD degree in Course 18, can be found at http://math.mit.edu/academics/grad/timeline/plan.php . Deviations associated with the Math-CSE degree (“18.CSD”) are as follows.

The Math-CSE doctoral program of study consists of at least five graduate-level subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects . Subjects taken as part of an MIT SM degree can be counted toward this requirement. Doctoral candidates are normally expected to take their major subjects at the Institute. The specific subjects will depend on the student’s thesis topic and background, and will be approved by the Chair of the Applied Mathematics Committee in the Mathematics department and CCSE.

The thesis committee composition requirements are identical to those of Course 18, with the additional requirement that either the advisor be a CCSE member or the committee contain at least two CCSE members.

Course 18 will award degrees under the Thesis field “Mathematics and Computational Science”.

Department of Nuclear Science & Engineering

NSE-CSE PhD candidates (“22.CSD”) must satisfy all NSE requirements for doctoral students, including passing the 22.15 module final exam with a satisfactory grade and completing an NSE Field of Specialization requirement. A complete description of the NSE doctoral program  and its requirements can be found at: http://web.mit.edu/nse/education/grad/phd.html .

Deviations associated with the NSE-CSE degree are as follows. The oral exam committee must include at least two CCSE-affiliated faculty members (one or both of whom may be NSE faculty members). The content of the oral exam must address some aspects related to computation.

In addition to satisfying a NSE Field of Specialization requirement, students pursuing the computation option must take at least five graduate-level subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects . Subjects taken as part of an MIT SM program can be counted toward this requirement. Each of these subjects can be applied towards either the Advanced Subject requirement or the Minor requirement (but not both).  None of these subjects can count towards the Field of Specialization requirement. Doctoral candidates are normally expected to take their major subjects at the Institute. The specific subjects will depend on the student’s thesis topic and background, and will be approved by thesis committee.

The thesis committee composition requirements are identical to those of Course 22, with the additional requirement that either the advisor be a CCSE member or the committee contain at least two CCSE members (who may be NSE faculty members).

In addition to approval from the Chair, Department Committee on Graduate Students, the complete thesis needs to be submitted to and approved by CCSE. Students should provide a copy of the thesis title page to the CCSE academic administrator for review and approval prior to submitting the final thesis.

Course 22 will award degrees under the thesis fields “Nuclear Engineering and Computation” and “Computational Nuclear Science and Engineering”.  Student may choose either; the requirements are identical.

Doctoral candidates in general may petition to change the name appearing on their degree certificates. However, petitions from students in the CSE-participating departments listed above to include the keywords ‘computation’ or ‘computational’ in the degree name will only be approved if the student has satisfied requirements listed above. The PhD thesis field “Computational Science and Engineering” will be reserved for students graduating from the standalone CSE PhD program.

Doctoral Degrees

A doctoral degree requires the satisfactory completion of an approved program of advanced study and original research of high quality..

Please note that the Doctor of Philosophy (PhD) and Doctor of Science (ScD) degrees are awarded interchangeably by all departments in the School of Engineering and the School of Science, except in the fields of biology, cognitive science, neuroscience, medical engineering, and medical physics. This means that, excepting the departments outlined above, the coursework and expectations to earn a Doctor of Philosophy and for a Doctor of Science degree from these schools are generally the same. Doctoral students may choose which degree they wish to complete.

Applicants interested in graduate education should apply to the department or graduate program conducting research in the area of interest. Some departments require a doctoral candidate to take a “minor” program outside of the student’s principal field of study; if you wish to apply to one of these departments, please consider additional fields you may like to pursue.

Below is a list of programs and departments that offer doctoral-level degrees.

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Computational and Systems Biology PhD Program

Computational and systems biology.

The field of computational and systems biology represents a synthesis of ideas and approaches from the life sciences, physical sciences, computer science, and engineering. Recent advances in biology, including the human genome project and massively parallel approaches to probing biological samples, have created new opportunities to understand biological problems from a systems perspective. Systems modeling and design are well established in engineering disciplines but are newer in biology. Advances in computational and systems biology require multidisciplinary teams with skill in applying principles and tools from engineering and computer science to solve problems in biology and medicine. To provide education in this emerging field, the Computational and Systems Biology (CSB) program integrates MIT's world-renowned disciplines in biology, engineering, mathematics, and computer science. Graduates of the program are uniquely prepared to make novel discoveries, develop new methods, and establish new paradigms. They are also well-positioned to assume critical leadership roles in both academia and industry, where this field is becoming increasingly important.

Computational and systems biology, as practiced at MIT, is organized around "the 3 Ds" of description, distillation, and design. In many research programs, systematic data collection is used to create detailed molecular- or cellular-level descriptions of a system in one or more defined states. Given the complexity of biological systems and the number of interacting components and parameters, system modeling is often conducted with the aim of distilling the essential or most important subsystems, components, and parameters, and of obtaining simplified models that retain the ability to accurately predict system behavior under a wide range of conditions. Distillation of the system can increase the interpretability of the models in relation to evolutionary and engineering principles such as robustness, modularity, and evolvability. The resulting models may also serve to facilitate rational design of perturbations to test understanding of the system or to change system behavior (e.g., for therapeutic intervention), as well as efforts to design related systems or systems composed of similar biological components.

CSB Faculty and Research

More than 70 faculty members at the Institute participate in MIT's Computational and Systems Biology Initiative (CSBi). These investigators span nearly all departments in the School of Science and the School of Engineering, providing CSB students the opportunity to pursue thesis research in a wide variety of different laboratories. It is also possible for students to arrange collaborative thesis projects with joint supervision by faculty members with different areas of expertise. Areas of active research include computational biology and bioinformatics, gene and protein networks, regulatory genomics, molecular biophysics, instrumentation engineering, cell and tissue engineering, predictive toxicology and metabolic engineering, imaging and image informatics, nanobiology and microsystems, biological design and synthetic biology, neurosystems biology, and cancer biology.

The CSB PhD Program

The CSB PhD program is an Institute-wide program that has been jointly developed by the Departments of Biology, Biological Engineering, and Electrical Engineering and Computer Science. The program integrates biology, engineering, and computation to address complex problems in biological systems, and CSB PhD students have the opportunity to work with CSBi faculty from across the Institute. The curriculum has a strong emphasis on foundational material to encourage students to become creators of future tools and technologies, rather than merely practitioners of current approaches. Applicants must have an undergraduate degree in biology (or a related field), bioinformatics, chemistry, computer science, mathematics, statistics, physics, or an engineering discipline, with dual-emphasis degrees encouraged.

CSB Graduate Education

All students pursue a core curriculum that includes classes in biology and computational biology, along with a class in computational and systems biology based on the scientific literature. Advanced electives in science and engineering enhance both the breadth and depth of each student's education. During their first year, in addition to coursework, students carry out rotations in multiple research groups to gain a broader exposure to work at the frontier of this field, and to identify a suitable laboratory in which to conduct thesis research. CSB students also serve as teaching assistants during one semester in the second year to further develop their teaching and communication skills and facilitate their interactions across disciplines. Students also participate in training in the responsible conduct of research to prepare them for the complexities and demands of modern scientific research. The total length of the program, including classwork, qualifying examinations, thesis research, and preparation of the thesis is roughly five years.

The CSB curriculum has two components. The first is a core that provides foundational knowledge of both biology and computational biology. The second is a customized program of electives that is selected by each student in consultation with members of the CSB graduate committee. The goal is to allow students broad latitude in defining their individual area of interest, while at the same time providing oversight and guidance to ensure that training is rigorous and thorough.

Core Curriculum

The core curriculum consists of three classroom subjects plus a set of three research rotations in different research groups. The classroom subjects fall into three areas described below.

Modern Biology (One Subject): A term of modern biology at MIT strengthens the biology base of all students in the program. Subjects in biochemistry, genetics, cell biology, molecular biology, or neurobiology fulfill this requirement. The particular course taken by each student will depend on their background and will be determined in consultation with graduate committee members.

Computational Biology (One Subject): A term of computational biology provides students with a background in the application of computation to biology, including analysis and modeling of sequence, structural, and systems data. This requirement can be fulfilled by 7.91[J] / 20.490[J] Foundations of Computational and Systems Biology.

Topics in Computational and Systems Biology (One Subject): All first-year students in the program participate in / 7.89[J] Topics in Computational and Systems Biology, an exploration of problems and approaches in the field of computational and systems biology through in-depth discussion and critical analysis of selected primary research papers. This subject is restricted to first-year PhD students in CSB or related fields in order to build a strong community among the class. It is the only subject in the program with such a limitation.

Research Group Rotations (Three Rotations): To assist students with lab selection and provide a range of research activities in computational and systems biology, students participate in three research rotations of one to two months' duration during their first year. Students are encouraged to gain experience in experimental and computational approaches taken across different disciplines at MIT.

Advanced Electives

The requirement of four advanced electives is designed to develop both breadth and depth. The electives add to the base of the diversified core and contribute strength in areas related to student interest and research direction. To develop depth, two of the four advanced electives must be in the same research area or department. To develop breadth, at least one of the electives must be in engineering and at least one in science. Each student designs a program of advanced electives that satisfies the distribution and area requirements in close consultation with members of the graduate committee.

Additional Subjects: As is typical for students in other doctoral programs at MIT, CSB PhD students may take classes beyond the required diversified core and advanced electives described above. These additional subjects can be used to add breadth or depth to the proposed curriculum, and might be useful to explore advanced topics relevant to the student's thesis research in later years. The CSB Graduate Committee works with each graduate student to develop a path through the curriculum appropriate for his or her background and research interests.

Training in the Responsible Conduct of Research: Throughout the program, students will be expected to attend workshops and other activities that provide training in the ethical conduct of research. This is particularly important in interdisciplinary fields such as computational and systems biology, where different disciplines often have very different philosophies and conventions. By the end of the fourth year, students will have had about 16 hours of training in the responsible conduct of research.

Qualifying Exams: In addition to coursework and a research thesis, each student must pass a written and an oral qualifying examination at the end of the second year or the beginning of the third year. The written examination involves preparing a research proposal based on the student's thesis research, and presenting the proposal to the examination committee. This process provides a strong foundation for the thesis research, incorporating new research ideas and refinement of the scope of the research project. The oral examination is based on the coursework taken and on related published literature. The qualifying exams are designed to develop and demonstrate depth in a selected area (the area of the thesis research) as well as breadth of knowledge across the field of computational and systems biology.

Thesis Research: Research will be performed under the supervision of a CSBi faculty member, culminating in the submission of a written thesis and its oral defense before the community and thesis defense committee. By the second year, a student will have formed a thesis advisory committee that they will meet with on an annual basis.

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The field of computational and systems biology represents a synthesis of ideas and approaches from the life sciences, physical sciences, computer science, and engineering. Recent advances in biology, including the human genome project and massively parallel approaches to probing biological samples, have created new opportunities to understand biological problems from a systems perspective. Systems modeling and design are well established in engineering disciplines but are newer in biology. Advances in computational and systems biology require multidisciplinary teams with skill in applying principles and tools from engineering and computer science to solve problems in biology and medicine. To provide education in this emerging field, the Computational and Systems Biology (CSB) program integrates MIT's world-renowned disciplines in biology, engineering, mathematics, and computer science. Graduates of the program are uniquely prepared to make novel discoveries, develop new methods, and establish new paradigms. They are also well-positioned to assume critical leadership roles in both academia and industry, where this field is becoming increasingly important.

Computational and systems biology, as practiced at MIT, is organized around "the 3 Ds" of description, distillation, and design. In many research programs, systematic data collection is used to create detailed molecular- or cellular-level descriptions of a system in one or more defined states. Given the complexity of biological systems and the number of interacting components and parameters, system modeling is often conducted with the aim of distilling the essential or most important subsystems, components, and parameters, and of obtaining simplified models that retain the ability to accurately predict system behavior under a wide range of conditions. Distillation of the system can increase the interpretability of the models in relation to evolutionary and engineering principles such as robustness, modularity, and evolvability. The resulting models may also serve to facilitate rational design of perturbations to test understanding of the system or to change system behavior (e.g., for therapeutic intervention), as well as efforts to design related systems or systems composed of similar biological components.

More than 70 faculty members at the Institute participate in MIT's Computational and Systems Biology Initiative (CSBi). These investigators span nearly all departments in the School of Science and the School of Engineering, providing CSB students the opportunity to pursue thesis research in a wide variety of different MIT laboratories. It is also possible for students to arrange collaborative thesis projects with joint supervision by faculty members with different areas of expertise. Areas of active research include behavioral genetics and genomics; bioengineering and neuroengineering; biological networks and machine learning; cancer systems biology; cellular biophysics; chemical biology and metabolomics; evolutionary and computational biology; microbiology and systems ecology; molecular biophysics and structural biology; precision medicine and medical genomics; quantitative imaging; regulatory genomics, epigenomics, and proteomics; single cell manipulations and measurement; stem cell and developmental systems biology; synthetic biology and biological design; and systems immunology.

The CSB PhD program is an Institute-wide program that has been jointly developed by the Departments of Biology, Biological Engineering, and Electrical Engineering and Computer Science. The program integrates biology, engineering, and computation to address complex problems in biological systems, and CSB PhD students have the opportunity to work with CSBi faculty from across the Institute. The curriculum has a strong emphasis on foundational material to encourage students to become creators of future tools and technologies, rather than merely practitioners of current approaches. Applicants must have an undergraduate degree in biology (or a related field), bioinformatics, chemistry, computer science, mathematics, statistics, physics, or an engineering discipline, with dual-emphasis degrees encouraged.

All students pursue a core curriculum that includes classes in biology and computational biology, along with a class in computational and systems biology based on the scientific literature. Advanced electives in science and engineering enhance both the breadth and depth of each student's education. During their first year, in addition to coursework, students carry out rotations in multiple research groups to gain a broader exposure to work at the frontier of this field, and to identify a suitable laboratory in which to conduct thesis research. CSB students also serve as teaching assistants during one semester in the second year to further develop their teaching and communication skills and facilitate their interactions across disciplines. Students also participate in training in the responsible conduct of research to prepare them for the complexities and demands of modern scientific research. The total length of the program, including classwork, qualifying examinations, thesis research, and preparation of the thesis is roughly five years.

The CSB curriculum has two components. The first is a core that provides foundational knowledge of both biology and computational biology. The second is a customized program of electives that is selected by each student in consultation with members of the CSB graduate committee. The goal is to allow students broad latitude in defining their individual area of interest, while at the same time providing oversight and guidance to ensure that training is rigorous and thorough.

Core Curriculum

The core curriculum consists of three classroom subjects plus a set of three research rotations in different research groups. The classroom subjects are comprised of modern biology, computational biology, and a literature-based exploration of current research frontiers and paradigms, which is required of all first-year students in the program . Students also participate in three research rotations of one to two months' duration during their first year to expose them to a range of research activities in computation and systems biology, and to assist them in choosing a lab. Students are encouraged to gain experience in experimental and computational approaches taken across different disciplines at MIT.

Advanced Electives

To develop breadth and depth, add to the base of the diversified core, and contribute strength in areas related to their interest and research direction, students must take four advanced electives. Each student designs a program of advanced electives that satisfies the distribution and area requirements in close consultation with members of the graduate committee.

Additional Subjects

CSB PhD students may take classes beyond the required diversified core and advanced electives described above. These additional subjects can be used to add breadth or depth to the proposed curriculum, and might be useful to explore advanced topics relevant to the student's thesis research in later years. The CSB Graduate Committee works with each graduate student to develop a path through the curriculum appropriate for his or her background and research interests.

Training in the Responsible Conduct of Research

Throughout the program, students will be expected to attend workshops and other activities that provide training in the ethical conduct of research. This is particularly important in interdisciplinary fields such as computational and systems biology, where different disciplines often have very different philosophies and conventions. By the end of the fifth year, students will have had about 16 hours of training in the responsible conduct of research.

Qualifying Exams

In addition to coursework and a research thesis, each student must pass a written and an oral qualifying examination at the end of the second year or the beginning of the third year. The written examination involves preparing a research proposal based on the student's thesis research, and presenting the proposal to the examination committee. This process provides a strong foundation for the thesis research, incorporating new research ideas and refinement of the scope of the research project. The oral examination is based on the coursework taken and on related published literature. The qualifying exams are designed to develop and demonstrate depth in a selected area (the area of the thesis research) as well as breadth of knowledge across the field of computational and systems biology.

Thesis Research

Research will be performed under the supervision of a CSBi faculty member, culminating in the submission of a written thesis and its oral defense before the community and thesis defense committee. By the second year, a student will have formed a thesis advisory committee that they will meet with on an annual basis.

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Master of Science

The Institute’s requirements for the Master’s degree are 66 units of coursework plus an acceptable thesis. The Department requires that the 66 units consist of at least four subjects, at the “G” level. In addition, there is a requirement of one unit of Professional Perspective documented under 6.9940 [6.994] .

Master of Engineering

Students interested in this degree should contact the  Undergraduate Office . (Restricted to MIT EECS Undergraduates.)

Electrical Engineer or Engineer in Computer Science

For the Engineer degrees, 162 units are required, plus an acceptable thesis. Subjects in which the grade received is C, D, or F will not be accepted in fulfillment of the unit requirement for the EE or ECS degree. A Master’s thesis of superior quality may satisfy the EE or ECS thesis requirement. When the Master’s thesis grade is reported, the thesis supervisor is asked to certify that, should the EE or ECS degree eventually be sought, the Master’s thesis meets the required criteria for quality.

Doctor of Philosophy or Doctor of Science

The Institute’s basic requirements for the award of a doctorate are:

• Completion of a major program of advanced study, including qualifying examinations.
• Completion and oral defense of a thesis on original research.
• A minimum residence requirement of four terms of full time graduate work.
• Completion of a Minor Program.

Consult the current Catalog and Graduate School Manual for additional information. For further information on the Department’s Minor requirement and course descriptions see the current catalog.

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Prospective Ph.D. Students

• January 15th : Application deadline for Fall semester admissions.
• September 1st : Application deadline for Spring semester admissions
• Late Applications: Full consideration will be given to applications received by the deadline. Late applications are considered depending on availability of resources.

Application

Submit your application online through Graduate Division. The CS program requires the following Supplemental Documents to be uploaded with your application:

• Statement of Objectives/Purpose . This document explains why you wish to pursue a graduate degree and your career objectives.
• Three letters of reference . Enter the names and e-mail addresses of reference letter writers via the Graduate Division’s Supplemental Documents upload site. Your letter writers will submit their confidential letters directly to the Graduate Division.

When Graduate Division determines that your application is complete, your application will be forwarded to the ICS Department. Note: ICS does not collect the application fee, and thus cannot waive it. You may request a waiver from Graduate Division at [email protected], but they routinely deny such requests.

Minimum Requirements

An applicant may be admitted with a Bachelor’s degree or with an M.S. degree. Applicants with Bachelor’s degrees must satisfy the admission requirements of the ICS master’s program .

The GRE General Test is suggested but not required due to the logistical and financial challenges they pose to some students. If you send them, GRE scores should be sent to us directly from ETS (Institution code: 4867; Department code: 0402) .

International Students

Graduate Division requires that international applicants whose native language is not English take either the TOEFL or the IELTS . More information on the requirements is available on the English Proficiency page of the Graduate Division website . See also additional information for international applicants .

See the prospective FAQ . Questions about submitting an application should be directed to Graduate Division . Questions about the program should be emailed to ICS Graduate Chair .

MS in Data Science

MSDS students choose among the many introductory graduate courses offered to students in the PhD program. These courses cover areas of computer science, optimization, linear algebra and statistics for students that have not had prior exposure to this required course work. Master’s students are fully integrated in the academic activities of the department alongside the PhD students.

Students must complete the required 5 core courses, 4 electives, and a final project to complete the program. There are also three foundational courses that students can test out. For the students who test out of foundational courses, the minimum number of courses taken in the program is 9. For the students who take all foundational courses, it is 12. These foundational courses can be taken in the summer before the program starts. Finally, students will be able to engage in a variety of opportunities across the Data Science Institute research programs and partnerships during their residency in the program.

The Curriculum

Foundational courses:.

Interested students will have the opportunity to test out of each of the 3 foundation courses below. Each of the courses will be offered in the late summer and offered online before the start of the fall quarter.

• Computational Foundations for Data Science
• Mathematical Foundations for Data Science
• Statistical Foundations for Data Science

Core Courses:

• Introduction to Data Science
• Systems for Data and Computers/Data Design
• Data Interaction
• Introduction to ML and AI  or Foundations of Machine Learning and AI Part I
• Responsible Use of Data and Algorithms

Four graduate-level electives can be selected from a wide variety of courses in Data Science, Computer Science, Statistics and across the University.

The online application portal will begin accepting applications for Fall 2024 admission in early Fall 2023. To ensure full consideration, applicants should apply by the deadline. The program may accept applications after the deadline if the cohort is not filled.

Learn from the world’s № 1 university with MIT’s free and low-cost online courses

Qs world university rankings ranks mit № 1 in 11 subjects and № 2 in five others for 2024..

By Katherine Ouellette

For the 12th year in a row, MIT has been ranked as the № 1 university in the world by QS World University Rankings. The Institute has also placed first in 11 subject areas and second in five subject areas for 2024. With MIT Open Learning’s free and low-cost online courses and programs, anyone in the world can learn these top-ranked subjects.

The Institute received a №1 ranking in the following QS subject areas: Chemical Engineering; Civil and Structural Engineering; Computer Science and Information Systems; Data Science and Artificial Intelligence; Electrical and Electronic Engineering; Linguistics; Materials Science; Mechanical, Aeronautical, and Manufacturing Engineering; Mathematics; Physics and Astronomy; and Statistics and Operational Research.

MIT also placed second in five subject areas: Accounting and Finance; Architecture/Built Environment; Biological Sciences; Chemistry; and Economics and Econometrics.

Start learning today with the following free and low-cost online courses available through MIT OpenCourseWare, MITx , and MITx Micromasters.

Accounting and Finance

• Undergraduate courses on MIT OpenCourseWare
• Graduate courses on MIT OpenCourseWare
• Fundamentals of Entrepreneurial Finance on MITx  Online
• MITx MicroMasters Program in Finance (or take any of the five individual MITx courses on edX)

Architecture/Built Environment

• Urban Studies and Planning courses on MITx  Online
• MITx : A Global History of Architecture on edX
• MITx : Sustainable Building Design on edX

Biological Sciences

• MITx: Biology courses on edX

• MITx : General Chemistry I: Atoms, Molecules, and Bonding on edX
• MITx : General Chemistry II: Chemical Equilibrium, Kinetics, and Transition Metals on edX

Chemical Engineering

• Chemical Engineering courses on MITx  Online
• MITx : Making Biologic Medicines for Patients: The Principles of Biopharmaceutical Manufacturing on edX

Civil and Structural Engineering

Computer science and information systems.

• MITx : Computational Thinking Using Python XSeries Program on edX

Data Science and Artificial Intelligence

• MITx : Understanding the World Through Data on edX
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Economics and Econometrics

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Materials Science

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Mechanical, Aeronautical, and Manufacturing Engineering

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Mathematics

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Statistics and Operational Research

• Fundamentals of Statistics from MITx on edX

Adapted from an April 10 story published at https://news.mit.edu .

These course materials are available through MIT OpenCourseWare, MITx, and MITx MicroMasters, which are part of MIT Open Learning. OpenCourseWare offers free, online, open educational resources from more than 2,500 courses that span the MIT undergraduate and graduate curriculum. MITx offers hundreds of high-quality massive open online courses adapted from the MIT classroom for learners worldwide. The MITx MicroMasters Programs provide an affordable, accelerated, and convenient path to a master’s degree. The credential itself is also valuable for professionals as they move through their careers.

Learn from the world’s № 1 university with MIT’s free and low-cost online courses was originally published in MIT Open Learning on Medium, where people are continuing the conversation by highlighting and responding to this story.

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MIT’s Master of Applied Science in Data, Economics, and Design of Policy program adds a public policy track

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MIT’s Abdul Latif Jameel Poverty Action Lab (J-PAL) and Department of Economics have announced an expansion of their jointly administered Master of Applied Science in Data, Economics, and Design of Policy (DEDP) program . This expansion adds a new public policy track to complement the existing international development track, opening up new avenues for student learning and research. 

Designed to tackle poverty alleviation and other pressing policy challenges in the United States and other high-income countries, the curriculum of the new track spans a diverse set of issues, from domestic concerns like minimum wage and consumer welfare to global matters including trade, climate change, and immigration. Applications for the public policy track will open this fall, with the inaugural cohort set to arrive on MIT’s campus in spring 2026.

The DEDP program, led by MIT professors and Nobel laureates Abhijit Banerjee and Esther Duflo, along with professors Sara Fisher Ellison and Benjamin Olken, was established with the mission of equipping diverse cohorts of talented professionals with the knowledge and skills to tackle poverty using evidence-based approaches. The new master’s degree track will support this mission while also underscoring the program’s commitment to addressing a broad array of critical challenges in the fight against poverty worldwide.

"The DEDP program has proven successful on many dimensions, and we are enthusiastic about leveraging its successes to address a broader set of social challenges,” says Ellison, a faculty lead for the program. “The public policy track will enable us to apply evidence-based methodology to poverty alleviation and other related issues in the context of high-income countries, as well. Given increasing levels of wealth and income inequality in these countries, we feel that the timing is opportune and the need is great."

The DEDP program distinguishes itself with an innovative admissions model that prioritizes demonstrated ability and motivation over traditional credentials, such as standardized tests and recommendation letters. To be eligible to apply to the master’s program, candidates must have earned a DEDP MicroMasters credential by passing five of the DEDP online courses. The courses are completely free to audit. Those who wish to earn a course certificate can pay a fee, which varies by the learner’s ability to pay, to take the proctored exam. While applications are reviewed holistically, performance in these classes is the primary factor in admissions decisions.

This approach democratizes access to higher education, enabling students from typically underrepresented backgrounds to demonstrate their potential for success. Notably, the program has welcomed many students from nontraditional backgrounds, such as a student who enrolled directly from high school (and who is now a second-year PhD student in economics at MIT), reflecting the ambition of its faculty directors to make higher education more accessible.

Sofia Martinez, a graduate of the class of 2023 and now co-founder of Learning Alliance , says, "Without the MicroMasters paving the way, applying to MIT or any similar institution would have been unthinkable for us. Initially, my aim in taking the online courses wasn't to pursue the residential program; it was only after witnessing my own progress that I realized the possibility wasn't so distant after all. This sentiment resonates with many in our cohort, which is truly humbling.”

Since its launch in 2020, the DEDP master’s program has conferred degrees to 87 students from 44 countries, showcasing its global reach and the success of its admissions model. Upon arriving on campus, students embark on an accelerated master's program. They complete a full course load in the spring, followed by a capstone project in the summer, applying the theoretical knowledge and practical skills gained through the program at research and policy organizations.

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Master of Computer Science 2023 – 2024

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Every conceivable field of study is experiencing the impact of the digital transformation. From manufacturing to healthcare to education and beyond, industry demand for digital solutions will only increase. The shift presents exciting career opportunities and challenges for tomorrow’s workforce.  

UC Irvine has recognized the necessity of equipping and empowering tomorrow’s innovators with forward-thinking technical knowledge coupled with practical skillsets as the digital world takes shape. Discover how our professional Master’s in Computer Science program can pave an exciting career path for you. 

Discover the ICS Advantage

Connecting with top companies, collaborate with pioneering faculty, access to professional development.

Abundant opportunities ranging from networking, internships and careers await MCS students. Southern California is home to hundreds of start-ups and household tech companies whose work impacts multiple industries. Learn beyond the classroom.

Students will have ample opportunities to collaborate with faculty whose industry experience and real-world insights offers students a comprehensive learning experience, preparing them for real-world applications.  

Occupational knowledge is just one side of the career equation. Enhancing one’s marketability and soft skills to navigate the nuances of the work culture is critical to paving a successful career path. Our professional development team coaches MCS students in developing these skillsets, giving them the competitive edge. 

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