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Below is a list of the MIT Schwarzman College of Computing’s graduate degree programs. The Doctor of Philosophy (PhD) degree is awarded interchangeably with the Doctor of Science (ScD).

Prospective students apply to the department or program under which they want to register. Application instructions can be found on each program’s website as well as on the MIT Graduate Admissions website.

Center for Computational Science and Engineering

The Center for Computational Science and Engineering (CCSE) brings together faculty, students, and other researchers across MIT involved in computational science research and education. The center focuses on advancing computational approaches to science and engineering problems, and offers SM and PhD programs in computational science and engineering (CSE).

• Computational Science and Engineering, SM and PhD . Interdisciplinary master’s program emphasizing advanced computational methods and applications. The CSE SM program prepares students with a common core of computational methods that serve all science and engineering disciplines, and an elective component that focuses on particular applications. Doctoral program enables students to specialize in methodological aspects of computational science via focused coursework and a thesis which involves the development and analysis of broadly applicable computational approaches that advance the state of the art.
• Computational Science and Engineering, Interdisciplinary PhD. Doctoral program offered jointly with eight participating departments, focusing on the development of new computational methods relevant to science and engineering disciplines. Students specialize in a computation-related field of their choice through coursework and a doctoral thesis. The specialization in computational science and engineering is highlighted by specially crafted thesis fields. 

Department of Electrical Engineering and Computer Science

The largest academic department at MIT, the Department of Electrical Engineering and Computer Science (EECS) prepares hundreds of students for leadership roles in academia, industry, government and research. Its world-class faculty have built their careers on pioneering contributions to the field of electrical engineering and computer science — a field which has transformed the world and invented the future within a single lifetime. MIT EECS consistently tops the U.S. News & World Report and other college rankings and is widely recognized for its rigorous and innovative curriculum. A joint venture between the Schwarzman College of Computing and the School of Engineering, EECS (also known as Course 6) is now composed of three overlapping sub-units in electrical engineering (EE), computer science (CS), and artificial intelligence and decision-making (AI+D).

• Computation and Cognition, MEng*. Course 6-9P builds on the Bachelor of Science in Computation and Cognition to provide additional depth in the subject areas through advanced coursework and a substantial thesis.
• Computer Science, PhD
• Computer Science and Engineering, PhD
• Computer Science, Economics, and Data Science, MEng*. New in Fall 2022, Course 6-14P builds on the Bachelor of Science in Computer Science, Economics, and Data Science to provide additional depth in economics and EECS through advanced coursework and a substantial thesis.
• Computer Science and Molecular Biology, MEng*. Course 6-7P builds on the Bachelor of Science in Computer Science and Molecular Biology to provide additional depth in computational biology through coursework and a substantial thesis.
• Electrical Engineering, PhD
• Electrical Engineering and Computer Science, MEng* , SM* , and PhD . Master of Engineering program (Course 6-P) provides the depth of knowledge and the skills needed for advanced graduate study and for professional work, as well as the breadth and perspective essential for engineering leadership. Master of Science program emphasizes one or more of the theoretical or experimental aspects of electrical engineering or computer science as students progress toward their PhD.
• Electrical Engineer / Engineer in Computer Science.** For PhD students who seek more extensive training and research experiences than are possible within the master’s program.
• Thesis Program with Industry, MEng.* Combines the Master of Engineering academic program with periods of industrial practice at affiliated companies. 

* Available only to qualified EECS undergraduates. ** Available only to students in the EECS PhD program who have not already earned a Master’s and to Leaders for Global Operations students.

Institute for Data, Systems, and Society

The Institute for Data, Systems, and Society advances education and research in analytical methods in statistics and data science, and applies these tools along with domain expertise and social science methods to address complex societal challenges in a diverse set of areas such as finance, energy systems, urbanization, social networks, and health.

• Social and Engineering Systems, PhD. Interdisciplinary PhD program focused on addressing societal challenges by combining the analytical tools of statistics and data science with engineering and social science methods.
• Technology and Policy, SM . Master’s program addresses societal challenges through research and education at the intersection of technology and policy.
• Interdisciplinary Doctoral Program in Statistics . For students currently enrolled in a participating MIT doctoral program who wish to develop their understanding of 21st-century statistics and apply these concepts within their chosen field of study. Participating departments and programs: Aeronautics and Astronautics, Brain and Cognitive Sciences, Economics, Mathematics, Mechanical Engineering, Physics, Political Science, and Social and Engineering Systems.

Operations Research Center

The Operations Research Center (ORC) offers multidisciplinary graduate programs in operations research and analytics. ORC’s community of scholars and researchers work collaboratively to connect data to decisions in order to solve problems effectively — and impact the world positively.

In conjunction with the MIT Sloan School of Management, ORC offers the following degrees:

• Operations Research, SM and PhD . Master’s program teaches important OR techniques — with an emphasis on practical, real-world applications — through a combination of challenging coursework and hands-on research. Doctoral program provides a thorough understanding of the theory of operations research while teaching students to how to develop and apply operations research methods in practice.
• Business Analytics, MBAn. Specialized advanced master’s degree designed to prepare students for careers in data science and business analytics.

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 19Aug2024)

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.

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.

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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Admissions Requirements

The following are general requirements you should meet to apply to the MIT Sloan PhD Program. Complete instructions concerning application requirements are available in the online application.

General Requirements

• Bachelor's degree or equivalent
• A strong quantitative background (the Accounting group requires calculus)
• Exposure to microeconomics and macroeconomics (the Accounting group requires microeconomics)

A Guide to Business PhD Applications by Abhishek Nagaraj (PhD 2016) may be of interest.

Application Components

Statement of purpose.

Your written statement is your chance to convince the admissions committee that you will do excellent doctoral work and that you have the promise to have a successful career as an academic researcher. 

GMAT/GRE Scores

We require either a valid GMAT or valid GRE score. At-home testing is allowed. Your unofficial score report from the testing institution is sufficient for application. If you are admitted to the program, you will be required to submit your official test score for verification.    

We do not have a minimum score requirement. We do not offer test waivers. Registration information for the GMAT (code X5X-QS-21) and GRE (code 3510) may be obtained at www.mba.com and www.ets.org respectively.

TOEFL/IELTS Scores

We require either a valid TOEFL (minimum score 577 PBT/90 IBT ) or valid IELTS (minimum score 7) for all non-native English speakers. Your unofficial score report from the testing institution is sufficient for application. If you are admitted to the program, you will be required to submit your official test score for verification.    Registration information for TOEFL (code 3510) and IELTS may be obtained at www.toefl.org and www.ielts.org respectively.

The TOEFL/IELTS test requirement is waived only if you meet one of the following criteria:

Please do not contact the PhD Program regarding waivers, as none will be discussed. If, upon review, the faculty are interested in your application with a missing required TOEFL or IELTS score, we may contact you at that time to request a score.

Transcripts

We require unofficial copies of transcripts for each college or university you have attended, even if no degree was awarded. If these transcripts are in a language other than English, we also require a copy of a certified translation. In addition, you will be asked to list the five most relevant courses you have taken.

Letters of Recommendation

We require three letters of recommendation. Academic letters are preferred, especially those providing evidence of research potential. We allow for an optional  fourth recommendation, but no more than four recommendations are allowed.

Your resume should be no more than two pages. You may chose to include teaching, professional experience, research experience, publications, and other accomplishments in outside activities.

Writing Sample(s)

Applicants are encouraged to submit a writing sample. For applicants to the Finance group, a writing sample is required. There are no specific guidelines for your writing sample. Possible options include (but are not limited to) essays, masters’ theses, capstone projects, or research papers.

Video Essay

A video essay is required for the Accounting research group and optional for the Marketing and System Dynamics research groups. The essay is a short and informal video answering why you selected this research group and a time where you creatively solved a problem. The video can be recorded with your phone or computer, and should range from 2 to 5 minutes in length. There is no attention — zero emphasis! — on the production value of your video.  

Nondiscrimination Policy: The Massachusetts Institute of Technology is committed to the principle of equal opportunity in education and employment. For complete text of MIT’s Nondiscrimination Statement, please click  here .

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Bruce Tidor, PhD

Research highlights.

Research in the Tidor Group is focused on the analysis of complex biological systems at the molecular and network levels.

Research in the Tidor Group is focused on the analysis of complex biological systems at the molecular and network levels. Projects at the molecular level study the structure and properties of proteins, nucleic acids, and their complexes. Investigations probe the sources of stability and specificity that drive macromolecular folding, binding, and catalysis. Studies are aimed at dissecting the interactions responsible for the specific structure of folded proteins and the binding geometry of molecular complexes. The roles played by salt bridges, hydrogen bonds, side-chain packing, rotameric states, solvation, and the hydrophobic effect in native biomolecules are being explored, and strategies for re-casting these roles through structure-based molecular design are being developed. Work at the network level involves the study of biochemical regulatory networks and signal transduction pathways in cells. The development of approaches to relate network topology to functional characteristics is fundamental to this research. Significant effort is being applied to extracting the design principles for biological networks and to understanding the control functions implemented. The insights resulting from this work will provide a strong foundation for understanding biological systems; moreover, they will be useful for the development of therapies that ameliorate disease states, as well as for the construction of new synthetic systems from biological components. The methods of theoretical and computational biophysics and approaches from computer science, artificial intelligence, applied mathematics, and chemical and electrical engineering play fundamental roles in this work.

Areas I Research

Professor Tidor completed his Bachelor’s degree in Chemistry and Physics at Harvard College. After a Master of Science degree at the University of Oxford, UK as a Marshall Scholar, he returned to his Alma Mater at Harvard for his doctoral studies in Biophysics. Bruce Tidor spent four years as a Whitehead Fellow at the Whitehead Institute for Biomedical Research. He joined MIT as Assistant Professor of Chemistry in 1994, became Associate Professor of Biological Engineering and Computer Science in 2001, and Professor of Biological Engineering and Computer Science in 2005.

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Admission Steps

Computer science - phd, admission requirements.

Terms and Deadlines

Degree and GPA Requirements

Prerequisites

Additional standards for non-native english speakers, additional standards for international applicants.

For the 2025-2026 academic year

See 2024-2025 requirements instead

Fall 2025 quarter (beginning in September)

Priority deadline: February 14, 2025

Final submission deadline: June 16, 2025

International submission deadline: May 5, 2025

Winter 2026 quarter (beginning in January)

Final submission deadline: November 4, 2025

International submission deadline: September 8, 2025

Spring 2026 quarter (beginning in March)

Final submission deadline: February 3, 2026

International submission deadline: December 8, 2025

Summer 2026 quarter (beginning in June)

Final submission deadline: May 4, 2026

International submission deadline: February 23, 2026

Priority deadline: Applications will be considered after the Priority deadline provided space is available.

Final submission deadline: Applicants cannot submit applications after the final submission deadline.

Degrees and GPA Requirements

Bachelors degree: All graduate applicants must hold an earned baccalaureate from a regionally accredited college or university or the recognized equivalent from an international institution.

University GPA requirement: The minimum grade point average for admission consideration for graduate study at the University of Denver must meet one of the following criteria:

A cumulative 2.5 on a 4.0 scale for the baccalaureate degree.

A cumulative 2.5 on a 4.0 scale for the last 60 semester credits or 90 quarter credits (approximately two years of work) for the baccalaureate degree.

An earned master’s degree or higher from a regionally accredited institution or the recognized equivalent from an international institution supersedes the minimum GPA requirement for the baccalaureate.

A cumulative GPA of 3.0 on a 4.0 scale for all graduate coursework completed for applicants who have not earned a master’s degree or higher.

Prerequisite courses for the PhD include: COMP 1671 Introduction to Computer Science I, COMP 1672 Introduction to Computer Science II, COMP 2673 Introduction to Computer Science III, COMP 2300 Discrete Structures in Computer Science, COMP 2370 Introduction to Algorithms & Data Structures, and COMP 2691 Introduction to Computer Organization (or equivalent).

Official scores from the Test of English as a Foreign Language (TOEFL), International English Language Testing System (IELTS), C1 Advanced or Duolingo English Test are required of all graduate applicants, regardless of citizenship status, whose native language is not English or who have been educated in countries where English is not the native language. Your TOEFL/IELTS/C1 Advanced/Duolingo English Test scores are valid for two years from the test date.

The minimum TOEFL/IELTS/C1 Advanced/Duolingo English Test score requirements for this degree program are:

Minimum TOEFL Score (Internet-based test): 80

Minimum IELTS Score: 6.5

Minimum C1 Advanced Score: 176

Minimum Duolingo English Test Score: 115

Additional Information:

Read the English Language Proficiency policy for more details.

Read the Required Tests for GTA Eligibility policy for more details.

Per Student & Exchange Visitor Program (SEVP) regulation, international applicants must meet all standards for admission before an I-20 or DS-2019 is issued, [per U.S. Federal Register: 8 CFR § 214.3(k)] or is academically eligible for admission and is admitted [per 22 C.F.R. §62]. Read the Additional Standards For International Applicants policy for more details.

Application Materials

Transcripts, letters of recommendation.

Required Essays and Statements

We require a scanned copy of your transcripts from every college or university you have attended. Scanned copies must be clearly legible and sized to print on standard 8½-by-11-inch paper. Transcripts that do not show degrees awarded must also be accompanied by a scanned copy of the diploma or degree certificate. If your academic transcripts were issued in a language other than English, both the original documents and certified English translations are required.

Transcripts and proof of degree documents for postsecondary degrees earned from institutions outside of the United States will be released to a third-party international credential evaluator to assess U.S. education system equivalencies. Beginning July 2023, a non-refundable fee for this service will be required before the application is processed.

Upon admission to the University of Denver, official transcripts will be required from each institution attended.

Three (3) letters of recommendation are required.  Letters should be submitted by recommenders through the online application.

Essays and Statements

Personal statement instructions.

A personal statement of at least 300 words is required. Your statement should include information concerning your life, education, experiences, interests and reason for applying to DU.

Résumé Instructions

The résumé (or C.V.) should include work experience, research, and/or volunteer work.

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Your submitted materials will be reviewed once all materials and application fees have been received.

Our program can only consider your application for admission if our Office of Graduate Education has received all your online materials and supplemental materials by our application deadline.

Application Fee: $65.00 Application Fee

International Degree Evaluation Fee: $50.00 Evaluation Fee for degrees (bachelor's or higher) earned from institutions outside the United States.

Applicants should complete their Free Application for Federal Student Aid (FAFSA) by February 15. Visit the Office of Financial Aid for additional information.

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Music Technology and Computation

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Music technology is the field of scientific inquiry where practitioners study, discover, and develop new approaches to computational models of music that include data analysis, generative algorithms, interaction and performance systems (including hardware, input devices and sensors), conceptual and perceptual modeling, and tools for creative expression and music applications. 

Master of Science in Music Technology and Computation

The Master of Science in Music Technology and Computation is a one-year, thesis-based residential program that focuses on the study and development of computational models of music. The curriculum includes machine learning for music analysis and generation, real-time music interaction and performance systems, music information retrieval, audio signal processing, acoustics, and digital instrument design.

This program is available to MIT undergraduate students who will have completed a four-year Bachelor of Science degree and have strong preparation in technical subjects (computation, engineering, design) and music (theory, composition, performance, musicology and/or ethnomusicology).

With departmental approval, students select 66 units of graduate subjects in music, music technology, and restricted electives, including the colloquium in music technology and the research seminar. The Master of Science degree also requires 24 units of thesis credit. Candidates must be matched to an approved thesis advisor as part of the application process.

Graduates will be well prepared for endeavors that require advanced multidisciplinary skills combining music, engineering, computation, and design, such as careers in music production tools, digital musical instruments, interactive design, digital music services, or creative software development. Graduates will also be prepared to continue on to PhD programs in music technology, either at MIT or at peer institutions.

Master of Applied Science in Music Technology and Computation

This program is not accepting applications for the 2025-26 academic year.

The Master of Applied Science in Music Technology and Computation is a one-year, coursework-based, residential program that focuses on the study and development of computational models of music. The curriculum includes machine learning for music analysis and generation, real-time music interaction and performance systems, music information retrieval, and digital instrument design.

This program is intended for individuals with preparation in both music (theory, composition, performance, musicology and/or ethnomusicology) and technical subjects (computer science, engineering and/or mathematics).

With departmental approval, students select 90 units of graduate subjects in music, music technology, and restricted electives, including the colloquium in music technology. The first semester comprises foundational classes, while the second semester focuses on advanced subjects in music technology, including the completion of a capstone project.

Graduates will be well prepared for endeavors that require advanced multidisciplinary skills combining music, engineering, computation, and design, such as careers in music production tools, digital musical instruments, interactive design, digital music services, or creative software development.

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