phd program at mit

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PhD in Physics, Statistics, and Data Science

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Many PhD students in the MIT Physics Department incorporate probability, statistics, computation, and data analysis into their research. These techniques are becoming increasingly important for both experimental and theoretical Physics research, with ever-growing datasets, more sophisticated physics simulations, and the development of cutting-edge machine learning tools. The Interdisciplinary Doctoral Program in Statistics (IDPS)  is designed to provide students with the highest level of competency in 21st century statistics, enabling doctoral students across MIT to better integrate computation and data analysis into their PhD thesis research.

Admission to this program is restricted to students currently enrolled in the Physics doctoral program or another participating MIT doctoral program. In addition to satisfying all of the requirements of the Physics PhD, students take one subject each in probability, statistics, computation and statistics, and data analysis, as well as the Doctoral Seminar in Statistics, and they write a dissertation in Physics utilizing statistical methods. Graduates of the program will receive their doctoral degree in the field of “Physics, Statistics, and Data Science.”

Doctoral students in Physics may submit an Interdisciplinary PhD in Statistics Form between the end of their second semester and penultimate semester in their Physics program. The application must include an endorsement from the student’s advisor, an up-to-date CV, current transcript, and a 1-2 page statement of interest in Statistics and Data Science.

The statement of interest can be based on the student’s thesis proposal for the Physics Department, but it must demonstrate that statistical methods will be used in a substantial way in the proposed research. In their statement, applicants are encouraged to explain how specific statistical techniques would be applied in their research. Applicants should further highlight ways that their proposed research might advance the use of statistics and data science, both in their physics subfield and potentially in other disciplines. If the work is part of a larger collaborative effort, the applicant should focus on their personal contributions.

For access to the selection form or for further information, please contact the IDSS Academic Office at  [email protected] .

Required Courses

Courses in this list that satisfy the Physics PhD degree requirements can count for both programs. Other similar or more advanced courses can count towards the “Computation & Statistics” and “Data Analysis” requirements, with permission from the program co-chairs. The IDS.190 requirement may be satisfied instead by IDS.955 Practical Experience in Data, Systems, and Society, if that experience exposes the student to a diverse set of topics in statistics and data science. Making this substitution requires permission from the program co-chairs prior to doing the practical experience.

• IDS.190 – Doctoral Seminar in Statistics and Data Science ( may be substituted by IDS.955 Practical Experience in Data, Systems and Society )
• 6.7700[J] Fundamentals of Probability or
• 18.675 – Theory of Probability
• 18.655 – Mathematical Statistics or
• 18.6501 – Fundamentals of Statistics or
• IDS.160[J] – Mathematical Statistics: A Non-Asymptotic Approach
• 6.C01/6.C51 – Modeling with Machine Learning: From Algorithms to Applications or
• 6.7810 Algorithms for Inference or
• 6.8610 (6.864) Advanced Natural Language Processing or
• 6.7900 (6.867) Machine Learning or
• 6.8710 (6.874) Computational Systems Biology: Deep Learning in the Life Sciences or
• 9.520[J] – Statistical Learning Theory and Applications or
• 16.940 – Numerical Methods for Stochastic Modeling and Inference or
• 18.337 – Numerical Computing and Interactive Software
• 8.316 – Data Science in Physics or
• 6.8300 (6.869) Advances in Computer Vision or
• 8.334 – Statistical Mechanics II or
• 8.371[J] – Quantum Information Science or
• 8.591[J] – Systems Biology or
• 8.592[J] – Statistical Physics in Biology or
• 8.942 – Cosmology or
• 9.583 – Functional MRI: Data Acquisition and Analysis or
• 16.456[J] – Biomedical Signal and Image Processing or
• 18.367 – Waves and Imaging or
• IDS.131[J] – Statistics, Computation, and Applications

Grade Policy

C, D, F, and O grades are unacceptable. Students should not earn more B grades than A grades, reflected by a PhysSDS GPA of ≥ 4.5. Students may be required to retake subjects graded B or lower, although generally one B grade will be tolerated.

Unless approved by the PhysSDS co-chairs, a minimum grade of B+ is required in all 12 unit courses, except IDS.190 (3 units) which requires a P grade.

Though not required, it is strongly encouraged for a member of the MIT  Statistics and Data Science Center (SDSC)  to serve on a student’s doctoral committee. This could be an SDSC member from the Physics department or from another field relevant to the proposed thesis research.

Thesis Proposal

All students must submit a thesis proposal using the standard Physics format. Dissertation research must involve the utilization of statistical methods in a substantial way.

PhysSDS Committee

• Jesse Thaler (co-chair)
• Mike Williams (co-chair)
• Isaac Chuang
• Janet Conrad
• William Detmold
• Philip Harris
• Jacqueline Hewitt
• Kiyoshi Masui
• Leonid Mirny
• Christoph Paus
• Phiala Shanahan
• Marin Soljačić
• Washington Taylor
• Max Tegmark

Can I satisfy the requirements with courses taken at Harvard?

Harvard CompSci 181 will count as the equivalent of MIT’s 6.867.  For the status of other courses, please contact the program co-chairs.

Can a course count both for the Physics degree requirements and the PhysSDS requirements?

Yes, this is possible, as long as the courses are already on the approved list of requirements. E.g. 8.592 can count as a breadth requirement for a NUPAX student as well as a Data Analysis requirement for the PhysSDS degree.

If I have previous experience in Probability and/or Statistics, can I test out of these requirements?

These courses are required by all of the IDPS degrees. They are meant to ensure that all students obtaining an IDPS degree share the same solid grounding in these fundamentals, and to help build a community of IDPS students across the various disciplines. Only in exceptional cases might it be possible to substitute more advanced courses in these areas.

Can I substitute a similar or more advanced course for the PhysSDS requirements?

Yes, this is possible for the “computation and statistics” and “data analysis” requirements, with permission of program co-chairs. Substitutions for the “probability” and “statistics” requirements will only be granted in exceptional cases.

For Spring 2021, the following course has been approved as a substitution for the “computation and statistics” requirement:   18.408 (Theoretical Foundations for Deep Learning) .

The following course has been approved as a substitution for the “data analysis” requirement:   6.481 (Introduction to Statistical Data Analysis) .

Can I apply for the PhysSDS degree in my last semester at MIT?

No, you must apply no later than your penultimate semester.

What does it mean to use statistical methods in a “substantial way” in one’s thesis?

The ideal case is that one’s thesis advances statistics research independent of the Physics applications. Advancing the use of statistical methods in one’s subfield of Physics would also qualify. Applying well-established statistical methods in one’s thesis could qualify, if the application is central to the Physics result. In all cases, we expect the student to demonstrate mastery of statistics and data science.

Academic Programs

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MIT Doctoral Programs in Computational Science and Engineering

The Center for Computational Science and Engineering (CCSE) offers two doctoral programs in computational science and engineering (CSE) – one leading to a standalone PhD degree in CSE offered entirely by CCSE (CSE PhD) and the other leading to an interdisciplinary PhD degree offered jointly with participating departments in the School of Engineering and the School of Science (Dept-CSE PhD).

While both programs enable students to specialize at the doctoral level in a computation-related field via focused coursework and a thesis, they differ in essential ways. The standalone CSE PhD program is intended for students who intend to pursue research in cross-cutting methodological aspects of computational science. The resulting doctoral degree in Computational Science and Engineering is awarded by CCSE via the the Schwarzman College of Computing. In contrast, the interdisciplinary CSE PhD program is intended for students who are interested in computation in the context of a specific engineering or science discipline. For this reason, this degree is offered jointly with participating departments across the Institute; the interdisciplinary degree is awarded in a specially crafted thesis field that recognizes the student’s specialization in computation within the chosen engineering or science discipline.

For more information about CCSE’s doctoral programs, please explore the links on the left. Information about our application and admission process is available via the ‘ Admissions ‘ tab in our menu. MIT Registrar’s Office provides graduate tuition and fee rates as set by the MIT Corporation and the Graduate Admissions section of MIT’s Office of Graduate Education (OGE) website contains additional information about costs of attendance and funding .

Ph.D./Sc.D. Program

The Doctor of Philosophy and Doctor of Science degrees in Chemical Engineering are identical; students may choose for themselves the appellation they prefer. This traditional, research-based doctoral degree program provides a thorough grounding in the fundamental principles of chemical engineering, as well as an intensive research experience.

The Doctor of Science and the Doctor of Philosophy in Chemical Engineering are identical degree programs. Degree candidates may choose to be called a “doctor of philosophy” or a “doctor of science”.

The degree requires that you complete:

• the core curriculum in chemical engineering
• one chemical engineering H Level class
• the departmental biology requirement
• a minor program of related subjects outside of chemical engineering
• written and oral doctoral qualifying examinations
• the writing and oral defense of a thesis on original research

The core curriculum is:

• Numerical Methods in Chemical Engineering 10.34
• Chemical Engineering Thermodynamics 10.40
• Analysis of Transport Phenomena 10.50
• Chemical Reactor Engineering 10.65

The departmental biology requirement is fulfilled by completing an undergraduate subject equivalent to MIT 7.01x, either at MIT or at your undergraduate institution. Examples of minor programs for some recent doctoral students include applied mathematics, control theory, physical, organic or analytical chemistry, mechanical structure, power systems, process metallurgy, nuclear engineering, management, economics, music, ancient history and philosophy.

The normal duration of the degree program is five to six years. (Including an intermediate M.S. CEP degree normally has little effect on the duration.) A master’s degree is not required for entrance into the doctoral program, nor is the M.S. CEP required.

For incoming, first-year graduate students, academic advisors are members of the Committee for Graduate Students. When you select a research topic and begin your thesis, the research supervisor becomes your academic advisor. In general, students choose research advisors at the end of their first Fall semester at MIT. Should you wish to choose a research advisor from a department other than Chemical Engineering, you will also need to choose a co-advisor from the Chemical Engineering faculty.

Prior to Registration Day (Fall and Spring semesters), your subject selection must first be approved by your advisor before the Graduate Officer can authorize registration on Registration Day. Advisor approval should also be obtained for any subsequent subject add/drop actions during the term (no additional authorization by the Graduate Officer is required).

Degree programs

Mit offers a wide range of degrees and programs..

All graduate students, whether or not they are participating in an interdepartmental program, must have a primary affiliation with and be registered in a single department. Every applicant accepted by MIT is admitted through one of the graduate departments. MIT has a number of established interdepartmental programs, and there are many more opportunities for students to arrange interdepartmental programs with interested faculty members.

All MIT graduate degree programs have residency requirements, which reflect academic terms (excluding summer). Some degrees also require completion of an acceptable thesis prepared in residence at MIT, unless special permission is granted for part of the thesis work to be accomplished elsewhere. Other degrees require a pro-seminar or capstone experience.

Applicants interested in graduate education should apply to the department or graduate program conducting research in the area of interest. Below is an alphabetical list of all the available departments and programs that offer a graduate-level degree.

Interested in reading first-hand accounts of MIT graduate students from a variety of programs? Visit the Grad Blog . Prospective students who want to talk with a current student can reach out to their department(s) of interest for connections or, if they are interested in the MIT experience for diverse communities, can reach out to a GradDiversity Ambassador .

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Graduate Program

Pushing the Scholarly Frontier

PhD in Political Science

Our doctoral students are advancing political science as a discipline. They explore the empirical phenomena that produce new scholarly insights—insights that improve the way governments and societies function. As a result, MIT Political Science graduates are sought after for top teaching and research positions in the U.S. and abroad. Read where program alumni are working around the world.

How the PhD program works

The MIT PhD in Political Science requires preparation in two of these major fields:

• American Politics
• Comparative Politics
• International Relations
• Models and Methods
• Political Economy
• Security Studies

We recommend that you take a broad array of courses across your two major fields. In some cases, a single course may overlap across the subject matter of both fields. You may not use more than one such course to "double count" for the course distribution requirement. Keep in mind that specific fields may have additional requirements.

You are free to take subjects in other departments across the Institute. Cross-registration arrangements also permit enrollment in subjects taught in the Graduate School of Arts and Sciences at Harvard University and in some of Harvard's other graduate schools.

Requirements

1. number of subjects.

You will need two full academic years of work to prepare for the general examinations and to meet other pre-dissertation requirements. Typically, a minimum of eight graduate subjects are required for a PhD.

2. Scope and Methods

This required one-semester seminar for first-year students introduces principles of empirical and theoretical analysis in political science.

3. Statistics

You must successfully complete at least one class in statistics.

You must successfully complete at least one class in empirical research methods.

5. Philosophy

You must successfully complete at least one class in political philosophy.

6. Foreign language or advanced statistics

You must demonstrate reading proficiency in one language other than English by successfully completing two semesters of intermediate-level coursework or an exam in that language, or you must demonstrate your knowledge of advanced statistics by successfully completing three semesters of coursework in advanced statistics. International students whose native language is not English are not subject to the language requirement.

7. Field research

We encourage you to conduct field research and to develop close working ties with faculty members engaged in major research activities.

8. Second Year Paper/workshop

You must complete an article-length research paper and related workshop in the spring semester of the second year. The second-year paper often develops into a dissertation project.

9. Two examinations

In each of your two elected fields, you must take a general written and oral examination. To prepare for these examinations, you should take at least three courses in each of the two fields, including the field seminar.

10. Doctoral thesis

As a rule, the doctoral thesis requires at least one year of original research and data collection. Writing the dissertation usually takes a substantially longer time. The thesis process includes a first and second colloquium and an oral defense. Be sure to consult the MIT Specifications for Thesis Preparation as well as the MIT Political Science Thesis Guidelines . Consult the MIT academic calendar to learn the due date for final submission of your defended, signed thesis.

Questions? Consult the MIT Political Science Departmental Handbook or a member of the staff in the MIT Political Science Graduate Office .

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How to Apply to the MIT Sloan PhD Program

The 2024 application is closed. The next opportunity to apply will be for 2025 admission. The 2025 application will open in September 2024. 

More information on program requirements and application components

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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.

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Doctor of Philosophy in Brain and Cognitive Sciences Fields

Department of Brain and Cognitive Sciences

Students in the Department of Brain and Cognitive Sciences doctoral program complete the program requirements detailed below. In the first year, students register for 12 units of 9.921 Research in Brain and Cognitive Sciences in the fall and spring terms to conduct three laboratory rotations, each lasting 4 to 8 weeks. As students progress, they serve as teaching assistants for two courses, one in their second year and one in their third, registering for 12 units of 9.919 Teaching Brain and Cognitive Sciences each term.

In addition to coursework, students must pass the oral and written qualifying exams for doctoral candidacy. Upon passing the exams, students complete at least 222 additional units of  9.921 in preparation for their thesis.

Program Requirements

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Department of Linguistics and Philosophy

Ph.d. program.

The program of studies leading to the doctorate in philosophy provides subjects and seminars in such traditional areas as logic, ethics, metaphysics, epistemology, philosophy of science, philosophy of language, philosophy of mind, aesthetics, social and political philosophy, and history of philosophy. Interest in philosophical problems arising from other disciplines, such as linguistics, psychology, mathematics and physics, is also encouraged.

Before beginning dissertation research, students are required to take two years of coursework, including a proseminar in contemporary philosophy that all students must complete in their first year of graduate study. Students are also required to pass general examinations and demonstrate competence in the following areas: value theory, logic and the history of philosophy.

Interdisciplinary study is encouraged, and candidates for the doctorate may take a minor in a field other than philosophy. There is no general language requirement for the doctorate, except in those cases in which competence in one or more foreign language is needed to carry on research for the dissertation.

Below is a detailed description of the philosophy Ph.D. program. For information about applying, see our admissions page ; we have also compiled data on placement , retention, and average completion times .

1. Your Advisor

When you join the Department you will be assigned a faculty advisor who will supervise your course of study. Your advisor must approve your program at the beginning of each term, and you should keep them abreast of your progress and problems. When forming a Fifth Term Paper committee the chair of your committee becomes your advisor. Similarly, when you form a dissertation committee.

Your teachers will write comments on your performance in subjects which you complete. These comments will be placed in your file in the Department office (your file is open to you), and they will be discussed at a meeting of the faculty at the end of each term. You should see your advisor at the end of each term to review your progress.

You may change your advisor at any time. Similarly you may change the composition of your fifth year paper and dissertation committees, as well as adjust the topics of those projects. To make a change first ask the relevant faculty if they are willing, then notify the Chair of the Committee on Graduate Students (COGS).

The current composition of COGS is: Brad Skow (Chief Cog), Kieran Setiya , and Roger White .

2. Requirements

2.1 overall course requirements.

Students must pass (with a grade of C or higher) at least 10 graduate subjects in philosophy (unless you earn a minor, in which case see section 4 below ). At least 7 must be subjects at MIT.

Students may petition COGS to use undergraduate subjects at MIT to satisfy the overall course requirement (except: in the case of an undergraduate logic subject more advanced than 24.241, no petition is needed).

Students must take at least 2 subjects in philosophy at MIT during each term of their first year, and at least 1 subject in philosophy at MIT during each term of their second year. Normally, students take 4 subjects during their second year.

2.2 Teaching Requirement

All graduate students must acquire some teaching experience. This requirement is normally satisfied by serving as a Teaching Assistant in an undergraduate subject in philosophy at MIT.

2.3 Logic Requirement

The logic requirement may be satisfied by doing one of the following:

(a) Pass the half-term subject Logic for Philosophers with a grade of B or better. (b) Audit Logic I and complete the work (Logic I may not be taken for graduate credit). (c) Pass Logic II, Modal Logic, or Theory of Models. Other advanced logic classes may also be used, with COGS approval. (d) Submit to COGS a syllabus from a logic class completed elsewhere, with a grade of B+ or better, showing it equivalent to Logic I.

Students should complete the logic requirement by the end of their fourth semester.

2.4 Distribution Requirement

2.4.1 proseminar.

All first-year students are required to complete the two-semester sequence 24.400-24.401, Proseminar in Philosophy. The first semester is an intensive seminar on the foundations of analytic philosophy from Frege to roughly 1960. The second semester is an intensive seminar on highlights of analytic philosophy from roughly 1960 to the present. The two-semester sequence counts as two subjects.

2.4.2 History of Philosophy

Students must complete two graduate subjects in the history of philosophy. For the purposes of this requirement, the history of philosophy means philosophers or philosophical schools that flourished before 1879.

A subject that spends a substantial part of, but not all of, its time on history counts toward this requirement provided the student’s term paper focuses on the history part. If there is doubt about whether a subject qualifies, consult COGS.

History subjects designed for a mixture of graduate and undergraduate students, like 100-level courses at Harvard, also count.

COGS permission is required in order to satisfy this requirement by taking two subjects on the same philosopher. (COGS will likely reject using two subjects on Descartes’ Meditations to fulfill the history requirement; COGS will likely approve using two subjects on Kant, one focused on ethics, the other on metaphysics and epistemology.)

Students wishing to fulfill this requirement by some other means should contact COGS.

2.4.3 Value Theory

Students must complete one graduate subject in ethics or political philosophy or aesthetics.

2.4.4 Dissertation Seminar

Students must complete the year-long dissertation seminar. Normally this is done in the third year. Students wishing to delay it until their fourth year may do so with permission of the instructor.

2.5 Fifth Term Paper Requirement

By the end of a student’s third term (usually fall of the second year) the student should select a paper topic for their Fifth Term Paper and form a committee to advise them on their work. The committee will consist of two faculty members (a supervisor and a second reader). The proposed topic and names of committee members should be submitted to COGS before the end-of-term meeting.

During the student’s fourth term, the student, in consultation with the committee, should assemble a reading list on the chosen topic. As a guideline, the reading list might consist of roughly twenty papers or the equivalent; the faculty recognizes that lengths of lists will vary. The final list must be approved by the committee and submitted to COGS by the end-of-term meeting.

During the fifth term, the student will write a polished paper on the chosen topic, roughly 25 pages long, in consultation with their committee. After submitting a final version of the paper that the committee deems satisfactory, the student will sit for an oral examination with the committee on both the paper and, more generally, the paper’s topic, as defined by the reading list.

The fifth term paper project is graded pass-fail. Students must pass the oral exam by the end-of-term meeting of their fifth term. After a student passes the exam their committee will write a report on the project to be given to the student and placed in the student’s file. Successfully completing this project constitutes passing the written and oral general examination requirements imposed by MIT’s Graduate School.

2.6 Petitions

A student may petition COGS to waive a requirement in light of their special circumstances.

3. Independent Studies

While in the normal case a student’s 10 graduate subjects will be seminars, students may also take an independent study with a faculty member. Students wishing to register for 24.891 or 24.892 must obtain permission from the Chief COG. After talking with the faculty member they wish to supervise their independent study, the student should write a proposal describing how often they will meet, how long the meetings will last, a tentative list of readings, and the amount of writing they will do. The Chief COG will approve an independent study only if the amount of work proposed equals or exceeds the usual amount of work in a seminar.

Students can minor in a field outside philosophy of their choosing (for example, linguistics, psychology, science technology and society, physics, feminist theory…). To earn a minor in field X a student must (i) pass 3 graduate subjects in field X, (ii) pass one graduate philosophy subject on a topic related to field X, and (iii) obtain COGS approval. (It is best to seek approval before all 4 subjects have been taken.) A student may receive no more than two minors; in the case of two minors, a single philosophy subject may (in rare cases) be used to satisfy clause (ii) for both minors.

Students who earn a minor need only pass 8, rather than 10, graduate philosophy subjects (7 must be taken at MIT). The subject used to satisfy (ii) counts as one of these 8.

Our faculty uses pluses and minuses, but the grades on your official transcript will be straight letter grades. Here are the meanings that MIT assigns to the grades:

A Exceptionally good performance, demonstrating a superior understanding of the subject matter, a foundation of extensive knowledge, and a skillful use of concepts and/or materials.

B Good performance, demonstrating capacity to use the appropriate concepts, a good understanding of the subject matter, and an ability to handle the problems and material encountered in the subject.

C Adequate performance, demonstrating an adequate understandingof the subject matter, an ability to handle relatively simpleproblems, and adequate preparation for moving on to more advanced work in the field.

D Minimally acceptable performance.

When the faculty determines the status of a student in the program, it does so on the basis of a review of the student’s total performance, which includes weighing the strengths and weaknesses of the student’s whole record. Thus it is in principle possible to redeem a weakness in one area by excellence in others.

An Incomplete (a grade of I) indicates that a minor part of the subject requirements has not been fulfilled and that a passing grade is to be expected when the work is completed. The grade I for the term remains permanently on the student’s record even when the subject is completed. In subjects in which the major work is a term paper, students may earn an I for the subject only if they submit a draft to the instructor(s) by midnight on the day before the end of term meeting. If a student does not hand in a draft by midnight on the day before the end of term meeting, the instructor is required to give the student an F. (The end of term meeting is shortly after the beginning of exam week.)

Any uncompleted incompletes on registration day of the following term will be converted to an F.

6. Ph.D. Thesis

A student is normally not allowed to begin work on a Ph.D. thesis until they have completed all of the requirements listed above. Students must complete all of those requirements by the end of their fifth term; exceptions will be made only after petition to COGS.

Once a student has completed the requirements listed above, there is the option of taking a terminal Master’s Degree instead of the Ph.D. This requires completing a Master’s thesis — students should consult COGS for more details.

The Ph.D. thesis is a substantial piece of original and independent research that displays mastery of an area of philosophy. A student may plan to write a sustained piece of work on one topic; they may instead plan to write three or more papers on connected topics. By the second month of the student’s sixth term they will submit to COGS a short (three to five pages) description of the projected thesis.

When the plan is approved, COGS will appoint a thesis committee consisting of a thesis supervisor and two additional readers, who shall be members of the philosophy faculty chosen by the student and willing to undertake the responsibility. The student will then meet with the members of the thesis committee for discussion of the material to be dealt with in the thesis. COGS approval is required if the student wants to include a non-MIT professor, or an MIT professor who is not on the philosophy faculty, on the committee. COGS approval is also required for a committee whose members include fewer than two MIT philosophy faculty (and this will be approved only in exceptional circumstances).

The student will meet regularly with their thesis supervisor throughout the writing of the thesis, and will provide all members of the thesis committee with written work by the end of each term. This requirement holds for nonresident as well as resident students.

The following rules govern completion of the thesis.

6.1 Final Term

The student will meet with their thesis committee during the first week of the term to assess the feasibility of completing the thesis during that term. The student and the committee will agree on a table of contents for the thesis, and on a schedule of dates for meeting the following requirements; a copy of the contents and the schedule should be given to COGS.

6.1.1 MIT Deadline

MIT requires that the completed thesis be delivered to the Department office by a date set by the Registrar for all Departments. (Early in January for February degrees, early in May for June degrees.) The Department regards this requirement as met by delivery to the thesis committee by that date of what the student regards as the final draft of their thesis.

6.1.2 Thesis Defense

The student will meet privately with their thesis committee to defend the thesis and to discuss any needed revisions. This meeting constitutes the official oral examination of the thesis.

The private defense must be scheduled for a date which will leave time for the student to make revisions before the MIT deadline. Once a student has completed the oral examination, and made any requested revisions, the decision whether to recommend award of the PhD is made by unanimous vote of the thesis committee.

6.1.3 Public Defense

The public defense is open to all members of the Department and their guests; it is chaired by the thesis supervisor, and normally runs for an hour, starting with a twenty-minute presentation by the student of the main results of the thesis. The public defense is the one occasion on which the entire Department has an opportunity to learn about and participate in the student’s work, and is a central part of the Ph.D. program.

The public defense is to be held after the student’s committee has voted to recommend awarding the PhD. One week before the public defense, the student should email the revised version to the chief COG, to be made available to members of the Department. A copy of the abstract should be emailed to the Academic Administrator for distribution when announcing the public defense to the Department.

6.1.4 Final Library Copy

The final library copy must be given to the Departmental representative to MIT’s Committee on Graduate School Policy (CGSP) by the day before that committee’s end-of-term meeting at which it approves the final degree list.

6.2 September Degrees

Students who will be unable to complete their theses during the spring term may wish to petition COGS for consideration for award of the degree in September. Such petitions will be granted on condition that an appropriate thesis committee can be constituted to work with the student during the summer. A schedule analogous to that described under 6.1 — including the scheduling of private and public defenses — must be given to COGS by the end of the spring term. The final library copy of the thesis must be given to the Departmental representative to CGSP by the day before that committee’s September meeting at which it approves the September degree list.

7. Policies on Satisfactory Progress and Good Standing

A student is in good standing so long as they have not fallen behind on any deadline mentioned in this document. The most salient of these is the deadline for the 5th term paper.

If a student is not in good standing, they will be unable to use their travel funds. If a student is not in good standing or has received a grade of B or lower in two classes in the previous semester, they are at risk of failing to make satisfactory academic progress.

If a student is at risk of failing to make satisfactory academic progress, the faculty will discuss the matter at the next end of term of meeting. (If any of the student’s advisors are not present at the meeting, they will be consulted before any action is taken.) The faculty will consider the work the student has produced, or failed to produce, so far, and the progress it represents. If there are serious doubts about the student’s prospects of completing the PhD, which includes writing a thesis that meets the conditions in section 6 , the student’s academic progress will be deemed unsatisfactory, and they will be issued a written notice from the Chief COG. The notice will explain how the student’s progress is unsatisfactory, what the student should accomplish in the following semester in order to avoid an official warning from the Vice Chancellor, and what steps the faculty will take to help the student accomplish these things. If a student fails to meet the conditions of the notice by the end of the following semester, as determined by the faculty, the student will receive an official warning from the Vice Chancellor. This warning will explain why the student’s progress continues to be unsatisfactory, what the student should accomplish in the following semester in order to continue in the program, and what steps the faculty will take to help the student accomplish these things. If the student is in a position to receive a terminal Master’s Degree, the conditions for doing so will be detailed. If the student fails to meet the conditions of the warning by the end of the semester, as determined by the faculty, the student will be denied permission to continue in the program.

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This collection of MIT Theses in DSpace contains selected theses and dissertations from all MIT departments. Please note that this is NOT a complete collection of MIT theses. To search all MIT theses, use MIT Libraries' catalog .

MIT's DSpace contains more than 58,000 theses completed at MIT dating as far back as the mid 1800's. Theses in this collection have been scanned by the MIT Libraries or submitted in electronic format by thesis authors. Since 2004 all new Masters and Ph.D. theses are scanned and added to this collection after degrees are awarded.

MIT Theses are openly available to all readers. Please share how this access affects or benefits you. Your story matters.

If you have questions about MIT theses in DSpace, [email protected] . See also Access & Availability Questions or About MIT Theses in DSpace .

If you are a recent MIT graduate, your thesis will be added to DSpace within 3-6 months after your graduation date. Please email [email protected] with any questions.

Permissions

MIT Theses may be protected by copyright. Please refer to the MIT Libraries Permissions Policy for permission information. Note that the copyright holder for most MIT theses is identified on the title page of the thesis.

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The properties of amorphous and microcrystalline Ni - Nb alloys. 

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Randomized Data Structures: New Perspectives and Hidden Surprises 

Alumni Q&A: Aviva Aron-Dine

Graduating from MIT with a doctorate in economics in 2012, Aron-Dine has spent over a decade in roles at the National Economic Council, the Office of Management and Budget, and the Department of Health and Human Services, as well as leading health policy work at the Center on Budget and Policy Priorities. Today she is the Acting Assistant Secretary for Tax Policy, the top tax official at the Treasury Department, and directs the office in developing, recommending, and implementing Federal tax policy. In that role, she works closely with Greg Leiserson, her MIT classmate, who serves as the Deputy Assistant Secretary for Tax Analysis and directs the work of the office’s economists.  

Q:     What parts of your MIT training been most useful in your policy career? A:     Broadly speaking, there’s no question that the most useful part of my economics training has been the core conceptual framework for analyzing problems. Focusing on particular aspects of my MIT training, I’ve certainly benefited from having the tools to digest empirical research and from being able to pretty quickly determine (and, when necessary, explain) whether a particular paper should or shouldn’t move one’s priors.

Q:     How as your MIT training been LEAST useful?  What were the problems you faced that your Ph.D. didn’t prepare you for? A:     There are many skills I’ve needed to develop in government that it probably wasn’t the job of an economics PhD program to provide – for example, a variety of skills in managing people. But one particular skill I’ve had to learn is how to relate other ways of thinking and talking about economic problems to the economics toolkit. For example, in my current role, I interact a lot with people who approach clean energy tax incentives from an industry background, or from various engineering, natural science, or environmental policy backgrounds – and who know much more than I do about the particulars of the relevant markets and technologies. When they say something about how the market works that sounds off to me, I have to figure out whether that’s because it’s not in my native “language,” because they have good evidence that the market isn’t working the way it’s “supposed to,” or because I actually disagree.  

Q:     How would you compare being an economist at a think tank to an economist directly implementing public policy? A:     What I find most rewarding about working in government is the fact that some of my work involves directly solving problems that matter to people. Not to over-idealize, but sometimes, we make a decision and as a result more people get income support or health care, or greenhouse gas emissions are reduced, or the federal government collects more revenue.

Q:     What are the particular economic concepts that have served you best in describing and making policy?  Are there any examples of creating “a-ha” moments for policy makers with your economics training? A:     The experience that was both most heartening and most humbling for me as an economist in government was my time at HHS during a period of rapid price increases and some disruption in the ACA marketplaces (2015-early 2017). On the one hand, economists in the Administration were the most clear-eyed about the adjustment to a new equilibrium and about the fact that, given the structure of the ACA’s premium tax credits, adjustment would occur with very modest coverage loss – exactly what happened. On the other hand, we had a lot of trouble explaining why prices were so far off in the first place (especially once insurers had access to initial data), why the transition took so long, and some of the choices insurers made in the interim! A broad take-away for me was that the economics framework for thinking about equilibrium outcomes is powerful and important in real-world policy settings – but we should be humble about how long and messy the transition can be.

Q:     What are the particular important economic concepts that you have the hardest time translating to policy audiences? A:     As I said, I think equilibrium thinking is one of the more useful things economists bring to the table, sometimes one of the harder things to explain, and at the same time a place where some humility is warranted. In some of my prior roles, I’ve often been the only economist at the table. In my current role, my staff is a mix of lawyers and economists, and the lawyers are pretty used to working with economists. It would be interesting to ask them, what legal concept do you have the most trouble getting across to those economists?!

Q:     How can other economics alumni – both inside and outside of academia - best help inform effective policy making in the U.S.? A:     For an economist newly coming into government, one piece of advice I would give is to identify a non-economist working in your policy area who you think is smart, effective, and shares your values – and try really hard to make yourself useful to them. I’d also recommend being open to the idea that your contributions may be different than you’d expect. Among academic economists doing a short stint in government, I’ve seen people make major contributions through their ability to do finger exercise to roughly quantify things – often having nothing to do with economics or their particular areas of expertise. For economists in academia and looking to shape policy – I don’t have better advice than to do good research on important problems, and explain it clearly!  

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Graduate Public Service Internship Program (GPSI)

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Graduate Public Service Internship Program

Apply online – For full consideration for the GPSI program, you must complete a UIS Graduate Admission Application as well as the GPSI application (On UIS Application Portal, NOT THROUGH HANDSHAKE!). To begin your application to a graduate school program, please apply online at:

www.uis.edu/admissions/applytoday/

The GPSI internship experience…education you can put to work!

If you are interested in a public sector internship experience while earning a master’s degree from the University of Illinois Springfield, then you need to look no further than the Graduate Public Service Internship Program (GPSI) at the University of Illinois Springfield.

Located within the Center for State Policy and Leadership, GPSI is ranked as one of Illinois’ premier governmental internship programs. For 50 years this program has provided top-flight graduate students with a high quality graduate education, real world experience, and lifelong networking connections. Regardless of your academic background, you are eligible to apply. After completing their program requirements, many interns begin professional careers in the public sector at the federal, state or local levels; as well as in the private sector. As means to help interns integrate academic knowledge and professional work experience, all GPSI interns must complete a one credit hour mandatory GPSI seminar during the first semester in the program.

GPSI interns serve a 21-month paid public sector internship while working on their graduate degree at UIS. Benefits the interns receive include:

• A maximum of 24 credit hours tuition waiver per academic year
• An annual $300 allowance for professional development opportunities or resources
• A monthly stipend of $1,200/month during the academic year when working 20 hours/week
• A monthly stipend of $2,400/month during the summer when working full-time hours
• An annual $1,300 student fee waiver ($650 awarded for each fall and spring semester)

GPSI accepts applicants from all academic programs who have completed either an undergraduate or advanced degree. Applicants who are pursing an undergraduate degree must have been awarded the degree prior to starting the internship. For first round consideration, the GPSI file must be complete by March 31. Interviews will be held in April for internships that commence August 16th.

Apply online – For full consideration for the GPSI program, you must complete a UIS Graduate Admission Application as well as the GPSI application. To begin your application to a graduate school program, please apply online at:

Office of Graduate Intern Programs

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Telephone: (217) 206-6158

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E-mail: [email protected]

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School of Engineering welcomes new faculty

The School of Engineering welcomes 15 new faculty members across six of its academic departments. This new cohort of faculty members, who have either recently started their roles at MIT or will start within the next year, conduct research across a diverse range of disciplines.

Many of these new faculty specialize in research that intersects with multiple fields. In addition to positions in the School of Engineering, a number of these faculty have positions at other units across MIT. Faculty with appointments in the Department of Electrical Engineering and Computer Science (EECS) report into both the School of Engineering and the MIT Stephen A. Schwarzman College of Computing. This year, new faculty also have joint appointments between the School of Engineering and the School of Humanities, Arts, and Social Sciences and the School of Science.

“I am delighted to welcome this cohort of talented new faculty to the School of Engineering,” says Anantha Chandrakasan, chief innovation and strategy officer, dean of engineering, and Vannevar Bush Professor of Electrical Engineering and Computer Science. “I am particularly struck by the interdisciplinary approach many of these new faculty take in their research. They are working in areas that are poised to have tremendous impact. I look forward to seeing them grow as researchers and educators.”

The new engineering faculty include:

Stephen Bates joined the Department of Electrical Engineering and Computer Science as an assistant professor in September 2023. He is also a member of the Laboratory for Information and Decision Systems (LIDS). Bates uses data and AI for reliable decision-making in the presence of uncertainty. In particular, he develops tools for statistical inference with AI models, data impacted by strategic behavior, and settings with distribution shift. Bates also works on applications in life sciences and sustainability. He previously worked as a postdoc in the Statistics and EECS departments at the University of California at Berkeley (UC Berkeley). Bates received a BS in statistics and mathematics at Harvard University and a PhD from Stanford University.

Abigail Bodner joined the Department of EECS and Department of Earth, Atmospheric and Planetary Sciences as an assistant professor in January. She is also a member of the LIDS. Bodner’s research interests span climate, physical oceanography, geophysical fluid dynamics, and turbulence. Previously, she worked as a Simons Junior Fellow at the Courant Institute of Mathematical Sciences at New York University. Bodner received her BS in geophysics and mathematics and MS in geophysics from Tel Aviv University, and her SM in applied mathematics and PhD from Brown University.

Andreea Bobu ’17 will join the Department of Aeronautics and Astronautics as an assistant professor in July. Her research sits at the intersection of robotics, mathematical human modeling, and deep learning. Previously, she was a research scientist at the Boston Dynamics AI Institute, focusing on how robots and humans can efficiently arrive at shared representations of their tasks for more seamless and reliable interactions. Bobu earned a BS in computer science and engineering from MIT and a PhD in electrical engineering and computer science from UC Berkeley.

Suraj Cheema will join the Department of Materials Science and Engineering, with a joint appointment in the Department of EECS, as an assistant professor in July. His research explores atomic-scale engineering of electronic materials to tackle challenges related to energy consumption, storage, and generation, aiming for more sustainable microelectronics. This spans computing and energy technologies via integrated ferroelectric devices. He previously worked as a postdoc at UC Berkeley. Cheema earned a BS in applied physics and applied mathematics from Columbia University and a PhD in materials science and engineering from UC Berkeley.

Samantha Coday joins the Department of EECS as an assistant professor in July. She will also be a member of the MIT Research Laboratory of Electronics. Her research interests include ultra-dense power converters enabling renewable energy integration, hybrid electric aircraft and future space exploration. To enable high-performance converters for these critical applications her research focuses on the optimization, design, and control of hybrid switched-capacitor converters. Coday earned a BS in electrical engineering and mathematics from Southern Methodist University and an MS and a PhD in electrical engineering and computer science from UC Berkeley.

Mitchell Gordon will join the Department of EECS as an assistant professor in July. He will also be a member of the MIT Computer Science and Artificial Intelligence Laboratory. In his research, Gordon designs interactive systems and evaluation approaches that bridge principles of human-computer interaction with the realities of machine learning. He currently works as a postdoc at the University of Washington. Gordon received a BS from the University of Rochester, and MS and PhD from Stanford University, all in computer science.

Kaiming He joined the Department of EECS as an associate professor in February. He will also be a member of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). His research interests cover a wide range of topics in computer vision and deep learning. He is currently focused on building computer models that can learn representations and develop intelligence from and for the complex world. Long term, he hopes to augment human intelligence with improved artificial intelligence. Before joining MIT, He was a research scientist at Facebook AI. He earned a BS from Tsinghua University and a PhD from the Chinese University of Hong Kong.

Anna Huang SM ’08 will join the departments of EECS and Music and Theater Arts as assistant professor in September. She will help develop graduate programming focused on music technology. Previously, she spent eight years with Magenta at Google Brain and DeepMind, spearheading efforts in generative modeling, reinforcement learning, and human-computer interaction to support human-AI partnerships in music-making. She is the creator of Music Transformer and Coconet (which powered the Bach Google Doodle). She was a judge and organizer for the AI Song Contest. Anna holds a Canada CIFAR AI Chair at Mila, a BM in music composition, and BS in computer science from the University of Southern California, an MS from the MIT Media Lab, and a PhD from Harvard University.

Yael Kalai PhD ’06 will join the Department of EECS as a professor in September. She is also a member of CSAIL. Her research interests include cryptography, the theory of computation, and security and privacy. Kalai currently focuses on both the theoretical and real-world applications of cryptography, including work on succinct and easily verifiable non-interactive proofs. She received her bachelor’s degree from the Hebrew University of Jerusalem, a master’s degree at the Weizmann Institute of Science, and a PhD from MIT.

Sendhil Mullainathan will join the departments of EECS and Economics as a professor in July. His research uses machine learning to understand complex problems in human behavior, social policy, and medicine. Previously, Mullainathan spent five years at MIT before joining the faculty at Harvard in 2004, and then the University of Chicago in 2018. He received his BA in computer science, mathematics, and economics from Cornell University and his PhD from Harvard University.

Alex Rives  will join the Department of EECS as an assistant professor in September, with a core membership in the Broad Institute of MIT and Harvard. In his research, Rives is focused on AI for scientific understanding, discovery, and design for biology. Rives worked with Meta as a New York University graduate student, where he founded and led the Evolutionary Scale Modeling team that developed large language models for proteins. Rives received his BS in philosophy and biology from Yale University and is completing his PhD in computer science at NYU.

Sungho Shin will join the Department of Chemical Engineering as an assistant professor in July. His research interests include control theory, optimization algorithms, high-performance computing, and their applications to decision-making in complex systems, such as energy infrastructures. Shin is a postdoc at the Mathematics and Computer Science Division at Argonne National Laboratory. He received a BS in mathematics and chemical engineering from Seoul National University and a PhD in chemical engineering from the University of Wisconsin-Madison.

Jessica Stark joined the Department of Biological Engineering as an assistant professor in January. In her research, Stark is developing technologies to realize the largely untapped potential of cell-surface sugars, called glycans, for immunological discovery and immunotherapy. Previously, Stark was an American Cancer Society postdoc at Stanford University. She earned a BS in chemical and biomolecular engineering from Cornell University and a PhD in chemical and biological engineering at Northwestern University.

Thomas John “T.J.” Wallin joined the Department of Materials Science and Engineering as an assistant professor in January. As a researcher, Wallin’s interests lay in advanced manufacturing of functional soft matter, with an emphasis on soft wearable technologies and their applications in human-computer interfaces. Previously, he was a research scientist at Meta’s Reality Labs Research working in their haptic interaction team. Wallin earned a BS in physics and chemistry from the College of William and Mary, and an MS and PhD in materials science and engineering from Cornell University.

Gioele Zardini joined the Department of Civil and Environmental Engineering as an assistant professor in September. He will also join LIDS and the Institute for Data, Systems, and Society. Driven by societal challenges, Zardini’s research interests include the co-design of sociotechnical systems, compositionality in engineering, applied category theory, decision and control, optimization, and game theory, with society-critical applications to intelligent transportation systems, autonomy, and complex networks and infrastructures. He received his BS, MS, and PhD in mechanical engineering with a focus on robotics, systems, and control from ETH Zurich, and spent time at MIT, Stanford University, and Motional.

Related Stories

When the PhD path leads to career struggles

A doctoral degree is a major commitment. Think carefully.

I appreciated reading Kara Miller’s The Big Idea column “PhD: Pretty heavily disappointed” (Business, May 22), about people with doctoral degrees struggling to build careers in academia. It made me think back to a conversation I had when I was about to graduate from high school.

I happened to run into a former track coach of mine, and as we were reminiscing he asked me what I planned as a major in college. “History,” I responded. He said, “Why don’t you take some computer classes also? It never hurts to be able to do something useful.”

I did not reflect on his motivation at the time, but my track coach was a young guy, and he was probably giving me advice straight from his own life, as a parent trying to raise his own young children. I did take computer classes in college and ultimately received a PhD in chemical engineering. I always remember that conversation as being a kind of turning point.

Earning a doctoral degree is a life commitment of great proportion. It can take, as Miller notes, between four and seven years. If we think of working life as roughly between the ages of 22 and 65, then a PhD requires more than 10 percent of a person’s working life. People need to think carefully about that investment.

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Two powerful arguments in favor of the path of science, technology, engineering, and math are that there tend to be more STEM jobs for PhDs, and many universities’ STEM departments are generous in covering their PhD students’ tuition and cost of studies, including a stipend toward food, rent, and other expenses.

Stuart Gallant

Not much has changed in 30 years

As I prepared to graduate in 1995 with a doctor of education degree from the Harvard Graduate School of Education, my mother memorably said to me, “Of my four children, you are the one with the most education and the smallest salary.” Apparently not much has changed in 30 years.

I must congratulate these students, however, on following their passion rather than following the money. I can’t help but think that their lives, though stressful, may contain greater happiness.

Peggy Clark

Lawyers & electricians & philosophers, oh my!

Kara Miller’s column on the career challenges for people with doctoral degrees generated more than 260 comments on Boston.Globe.com. The following is an edited sample of readers’ reactions:

Lots of law school grads are underemployed as well. (PL)

So true, PL. The market in Massachusetts is flooded with talented lawyers seeking work. (Roforma)

Supply and demand, the market at work. (guk)

Investing in education and research in all fields is the hallmark of a society with staying power. Disinvesting from these endeavors signals decline and decay. (Massachusetts citizen)

Electricians, plumbers, mechanics, and other skilled technical professions have no problems getting $100k jobs with great benefits. (ramsen)

Not enough turnover from tenured professors, leaving little space for new faculty. Although the tenured, well-established professors are needed, it’s the junior faculty who are hungry and with new ideas that help build new programs. The whole graduate program model is a bad model. I worked two jobs, had my tuition and some type of minimal student health insurance and could barely cover the rent with my stipend, and the second job paid for everything else. Though I was working on many faculty projects, it was the faculty who said this would be good for me. Never did they say it was also good for them. (TravelerofNJ2)

I just retired from a tenured faculty position in science. I’m in my early 70s. I have colleagues who are still doing what they do well into their 70s, a couple approaching 80. There is no active incentive from the university to move the older faculty on, to make way for a new generation. (Lola-lola)

The next step is for adjuncts to go on strike across the nation and hold colleges and universities accountable. The current system is completely absurd. (Wordsmith2358)

Universities should be required to release disclosure data about the fate of their PhD graduates. (davidman820)

I knew an attorney who managed a Cheesecake Factory. She had worked in food services through school. As an attorney, she really did not make that much money and was not doing the field of law of her choice. How many real estate closings can you do without dying of boredom? She went into management in the food industry and makes the same salary. (Antietem)

It was always a question and puzzling to me why people study philosophy. (Blazer27)

Globe Opinion

Suggestions or feedback?

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Modeling the threat of nuclear war

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It’s a question that occupies significant bandwidth in the world of nuclear arms security: Could hypersonic missiles, which fly at speeds of least five times the speed of sound, increase the likelihood of nuclear war?

Eli Sanchez, who recently completed his doctoral studies at MIT's Department of Nuclear Science and Engineering (NSE), explored these harrowing but necessary questions under the guidance of Scott Kemp , associate professor at NSE and director of the MIT Laboratory for Nuclear Security and Policy .

A well-rounded interest in science

Growing up in the small railroad town of Smithville, Texas, Sanchez fell in love with basic science in high school. He can’t point to any one subject — calculus, anatomy, physiology — they were all endlessly fascinating. But physics was particularly appealing early on because you learned about abstract models and saw them play out in the real world, Sanchez says. “Even the smallest cellular functions playing out on a larger scale in your own body is cool,” he adds, explaining his love of physiology.

Attending college at the University of Texas in Dallas was even more rewarding, as he could soak in the sciences and feed an insatiable appetite. Electricity and magnetism drew Sanchez in, as did quantum mechanics. “The reality underlying quantum is so counterintuitive to what we expect that the subject was fascinating. It was really cool to learn these very new and sort of foreign rules,” Sanchez says.

Stoking his interest in science in his undergraduate years, Sanchez learned about nuclear engineering outside of the classroom, and was especially intrigued by its potential for mitigating climate change. A professor with a specialty in nuclear chemistry fueled this interest and it was through a class in radiation chemistry that Sanchez learned more about the field.

Graduating with a major in chemistry and a minor in physics, Sanchez married his love of science with another interest, computational modeling, when he pursued an internship at Oak Ridge National Laboratory. At Oak Ridge, Sanchez worked on irradiation studies on humans by using computational models of the human body.

Work on nuclear weapons security at NSE

After Oak Ridge, Sanchez was pretty convinced he wanted to work on computational research in the nuclear field in some way. He appreciates that computational models, when done well, can yield accurate forecasts of the future. One can use models to predict failures in nuclear reactors, for example, and prevent them from happening.

After test-driving a couple of research options at NSE, Sanchez worked in the field of nuclear weapons security.

Experts in the field have long believed that the weapons or types of delivery systems like missiles and aircraft will affect the likelihood that states will feel compelled to start a nuclear war. The canonical example is a multiple independently-targetable reentry vehicle (MIRV) system, which deploys multiple warheads on the same missile. If one missile can take out one warhead, it can destroy five or 10 warheads with just one MRV system. Such a weapons capability, Sanchez points out, is very destabilizing because there’s a strong incentive to attack first.

Similarly, experts in nuclear arms control have been suggesting that hypersonic weapons are destabilizing, but most of the reasons have been speculative, Sanchez says. “We’re putting these claims to technical scrutiny to see if they hold up.”

One way to test these claims is by focusing on flight paths. Hypersonic missiles have been considered destabilizing because it’s impossible to determine their trajectories. Hypersonic missiles can turn as they fly, so they have destination ambiguity. Unlike ballistic missiles, which have a fixed trajectory, it’s not always apparent where hypersonic missiles are going. When the final target of a missile is unclear it is easy to assume the worst: “They could be mistaken for attacks against nuclear weapons or nuclear command-and-control structures or against national capitals,” Sanchez says, “it could look much more serious than it is, so it could prompt the nation that’s being attacked to respond in a way that will escalate the situation.”

Sanchez’s doctoral work included modeling the flights of hypersonic weapons to quantify the ambiguities that could lead to escalation. The key was to evaluate the area of ambiguity for missiles with given sets of properties. Part of the work also involved making recommendations that prevent hypersonic weapons from being used in destabilizing ways. A couple of these suggestions included arming hypersonic missiles with conventional (rather than nuclear) warheads and to create no-fly zones around world capitals.

Helping underserved students

Sanchez’s work at NSE was not limited to his doctoral studies alone. Along with NSE postdoc Rachel Bielajew PhD ’24, he started the Graduate Application Assistance Program (GAAP), which helps mitigate some of the disadvantages that underrepresented students are likely to encounter.

The son of a Latino father and middle-class parents who were themselves the first in their families to graduate from college, Sanchez considers himself fortunate. But he admits that unlike many of his peers, he found graduate school difficult to navigate. “That gave me an appreciation for the position that a lot of people coming from different backgrounds where there’s less higher education in the family might face,” Sanchez says.

GAAP’s purpose is to lessen some of these barriers and to connect potential applicants to current NSE graduate students so they can ask questions whose answers might paint a clearer picture of the landscape. Sanchez stepped down after two years of co-chairing the initiative but he continues as mentor. Questions he fields range from finding a research/lab fit to funding opportunities.

As for opportunities Sanchez himself will follow: a postdoctoral fellowship in the Security Studies Program in the Department of Political Science at MIT.

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• Graduate, postdoctoral
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