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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 .

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The largest graduate program in MIT’s School of Engineering, EECS has about 700 graduate students in the doctoral program at any given time. Those students conduct groundbreaking research across a wide array of fields alongside world-class faculty and research staff, build lifelong mentorship relationships and drive progress in every sector touched by electrical engineering, computer science, and artificial intelligence and decision-making.

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).

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Through intellectual rigor and experiential learning, this full-time, two-year MBA program develops leaders who make a difference in the world.

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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.  

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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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The department offers programs covering a broad range of topics leading to the Doctor of Philosophy and the Doctor of Science degrees (the student chooses which to receive; they are functionally equivalent). Candidates are admitted to either the Pure or Applied Mathematics programs but are free to pursue interests in both groups. Of the roughly 125 Ph.D. students, about 2/3 are in Pure Mathematics, 1/3 in Applied Mathematics.

The two programs in Pure and Applied Mathematics offer basic and advanced classes in analysis, algebra, geometry, Lie theory, logic, number theory, probability, statistics, topology, astrophysics, combinatorics, fluid dynamics, numerical analysis, mathematics of data, and the theory of computation. In addition, many mathematically-oriented courses are offered by other departments. Students in Applied Mathematics are especially encouraged to take courses in engineering and scientific subjects related to their research.

All students pursue research under the supervision of the faculty , and are encouraged to take advantage of the many seminars and colloquia at MIT and in the Boston area.

Degree Requirements

Degree requirements consist of:

• Oral qualifying exam
• Classroom teaching
• Original thesis and defense

Prospective students are invited to consult the graduate career timeline for more information, and to read about the application procedure .

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Graduate Study at SHASS

World-class graduate studies.

SHASS offers five doctoral and four master’s programs.

Doctoral programs

Our top-ranked PhD program sets the standard for graduate economics training across the country. Graduate students work closely with our world-class faculty to develop their own research and prepare to make impactful contributions to the field.

Our doctoral program enrolls 20-24 full-time students each year and students complete their degree in five to six years. Students undertake core coursework in microeconomic theory, macroeconomics, and econometrics, and are expected to complete two major and two minor fields in economics. Beyond the classroom, doctoral students work in close collaboration with faculty to develop their research capabilities, gaining hands-on experience in both theoretical and empirical projects.

Explore PhD program

History, Anthropology, and STS (HASTS)

The doctoral program in History, Anthropology, and Science, Technology, and Society (HASTS) at MIT, founded in 1988, is a unique interdisciplinary academic community devoted to studying the social, cultural, and political life of science and technology. HASTS faculty work with students to develop original scholarship on the historical foundations and contemporary implications of scientific and technological knowledge and practice.

As a culmination of their work, HASTS students complete dissertations that intervene in scholarly and public conversations about the role of science in society. After graduation, students go on to careers in academia, public service, and private industry.

Explore HASTS

Linguistics

Our 5-year PhD program is designed to introduce students to the basic concepts and results of research in generative linguistics, so that they can begin productively contributing to the department’s research activities. We have found that the best way to achieve this goal is for students to work from the very beginning on problems that are relevant to real-life research.

The program is rigorous and quite demanding of students’ time and energy. A high level of commitment and concentration is required to complete it successfully. The program also contains a relatively large number of required courses. We have found that this extra effort pays off in the long run, since students are exposed to a richer mix of research topics and methods. This also means that our students attain a high level of competence in more than one area, and thus qualify for academic and other positions in more than one specialty.

Explore Linguistics

From scallop fishing in New Bedford to deforestation in the tropics, “our goal is to get some empirical traction on the problem,” says Economics PhD student Aaron Berman.

Our program 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 write a fifth term pre-dissertation paper and demonstrate competence in the following areas: value theory, logic and the history of philosophy.

Explore Philosophy

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.

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, or Security Studies. We recommend that you take a broad array of courses across your two major fields.

Explore Political Science

Philosophy doctoral student Abe Mathew is both studying philosophy and questioning some of its deeply-held ideas.

Master’s programs

Data, economics, and design of policy.

The international fight against poverty is more data driven than ever before. Producing and understanding rigorous evidence has become increasingly critical for those seeking to affect change globally, but opportunities to acquire these skills remain limited.

As the first master’s program to be offered by MIT’s Department of Economics, the master’s program in Data, Economics, and Design of Policy (DEDP) is designed to meet this rising demand. Jointly run by the Economics Department and the Abdul Latif Jameel Poverty Action Lab (J-PAL ), the program equips development professionals from across the globe with the practical skills and theoretical knowledge needed to tackle some of the world’s most pressing challenges.

Explore Data, Economics, and Design of Policy

MIT Indigenous Language Initiative (Linguistics)

The MIT Indigenous Languages Initiative is a special master’s program in linguistics for members of communities whose languages are threatened. The goal of the program is to provide its graduates with the linguistic knowledge that will help them in efforts to keep their communities’ languages alive.

In addition, the MIT Indigenous Language Initiative offers expanded opportunities for students and faculty to become involved in indigenous and endangered languages. They do this through working with native speaker linguists in the master’s program and also with outside groups.

Explore Indigenous Language Initiative

The MIT Political Science master’s program prepares students to uncover essential insights into the workings of societies and governments in the 21st century. Master’s students develop the skills and knowledge to evaluate and promote effective public policies.

The one-year MIT Master of Science in Political Science is designed for students who want to build proficiency in applied research so that they can pursue successful careers in government, business, and public policy. Students interested in an academic career should read more about the PhD in Political Science.

Science Writing

The MIT Graduate Program in Science Writing (GPSW) is one of the world’s premier master’s programs in science journalism and communication. Set within a community of world-renowned scientists, cutting-edge facilities, and groundbreaking research, our one-year program focuses on introducing students to science communication across a broad range of media, including news and feature reporting, podcasting, data journalism, and documentary film.

During their year here, students learn fundamental research and reporting skills and produce publishable works of print, audio, video, and interactive journalism. Our curriculum teaches students how to interpret and explain science to the wider public, to place research and researchers within their social and historical contexts, and to create pieces that balance hard analysis with creativity and style.

Explore Science Writing

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

More resources

Learn more about MIT graduate studies at the Office of Graduate Education .

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Graduate Studies in Chemical Engineering

MIT Chemical Engineering gives graduate students incomparable opportunities to immerse themselves in the research they are most interested in. Whether your dream is to work in academia, industry,  or to create your own company, we can get you there.

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Creating connection with science communication

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Before completing her undergraduate studies, Sophie Hartley, a student in MIT’s Graduate Program in Science Writing, had an epiphany that was years in the making.

“The classes I took in my last undergraduate semester changed my career goals, but it started with my grandfather,” she says when asked about what led her to science writing. She’d been studying comparative human development at the University of Chicago, which Hartley describes as “a combination of psychology and anthropology,” when she took courses in environmental writing and digital science communications.

“What if my life could be about learning more of life’s intricacies?” she thought.

Hartley’s grandfather introduced her to photography when she was younger, which helped her develop an appreciation for the natural world. Each summer, they would explore tide pools, overgrown forests, and his sprawling backyard. He gave her a camera and encouraged her to take pictures of anything interesting.

“Photography was a door into science journalism,” she notes. “It lets you capture the raw beauty of a moment and return to it later.”

Lasting impact through storytelling

Hartley spent time in Wisconsin and Vermont while growing up. That’s when she noticed a divide between rural communities and urban spaces. She wants to tell stories about communities that are less likely to be covered, and “connect them to people in cities who might not otherwise understand what’s happening and why.”

People have important roles to play in arresting climate change impacts, improving land management practices and policies, and taking better care of our natural resources, according to Hartley. Challenges related to conservation, land management, and farming affect us all, which is why she believes effective science writing is so important.

“We’re way more connected than we believe or understand,” Hartley says. “Climate change is creating problems throughout the entire agricultural supply chain.”

For her news writing course, Hartley wrote a  story about how flooding in Vermont led to hay shortages, which impacted comestibles as diverse as goat cheese and beef. “When the hay can’t dry, it’s ruined,” she says. “That means cows and goats aren’t eating, which means they can’t produce our beef, milk, and cheese.”

Ultimately, Hartley believes her work can build compassion for others while also educating people about how everything we do affects nature and one another.

“The connective tissues between humans persist,” she said. “People who live in cities aren’t exempt from rural concerns.”

Creating connections with science writing

During her year-long study in the MIT Graduate Program in Science Writing, Hartley is also busy producing reporting for major news outlets.

Earlier this year, Hartley authored a piece for  Ars Technica that explored ongoing efforts to develop technology aimed at preventing car collisions with kangaroos. As Hartley reported, given the unique and unpredictable behavior of kangaroos, vehicle animal detection systems have proven ineffective. That’s forced Australian communities to develop alternative solutions, such as virtual fencing, to keep kangaroos away from the roads.

In June, Hartley co-produced a story for  GBH News with Hannah Richter, a fellow student in the science writing program. They reported on how and why officials at a new Peabody power plant are backtracking on an earlier pledge to run the facility on clean fuels.

The story was a collaboration between GBH News and the investigative journalism class in the science writing program. Hartley recalls wonderful experience working with Richter. “We were able to lean on each other’s strengths and learn from each other,” she says. “The piece took a long time to report and write, and it was helpful to have a friend and colleague to continuously motivate me when we would pick it back up after a while.”

Co-reporting can also help evenly divide what can sometimes become a massive workload, particularly with deeply, well-researched pieces like the Peabody story. “When there is so much research to do, it’s helpful to have another person to divvy up the work,” she continued. “It felt like everything was stronger and better, from the writing to the fact-checking, because we had two eyes on it during the reporting process.”

Hartley’s favorite piece in 2024 focused on beech leaf disease, a deadly pathogen devastating North American forests. Her story, which was later published in  The Boston Globe Magazine , followed a team of four researchers racing to discover how the disease works. Beech leaf disease kills swiftly and en masse, leaving space for invasive species to thrive on forest floors. Her interest in land management and natural resources shines through in much of her work.

Local news organizations are an endangered species as newsrooms across America shed staff and increasingly rely on aggregated news accounts from larger organizations. What can be lost, however, are opportunities to tell small-scale stories with potentially large-scale impacts. “Small and rural accountability stories are being told less and less,” Hartley notes. “I think it’s important that communities are aware of what is happening around them, especially if it impacts them.”

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More durable metals for fusion power reactors

For many decades, nuclear fusion power has been viewed as the ultimate energy source. A fusion power plant could generate carbon-free energy at a scale needed to address climate change. And it could be fueled by deuterium recovered from an essentially endless source — seawater. Decades of work and billions of dollars in research funding have yielded many advances, but challenges remain. To Ju Li, the TEPCO Professor in Nuclear Science and Engineering and a professor of materials science and engineering at MIT, there are still two big challenges. The first is to build a fusion power plant that generates more energy than is put into it; in other words, it produces a net output of power. Researchers worldwide are making progress toward meeting that goal. The second challenge that Li cites sounds straightforward: “How do we get the heat out?” But understanding the problem and finding a solution are both far from obvious. Research in the MIT Energy Initiative (MITEI) includes development and testing of advanced materials that may help address those challenges, as well as many other challenges of the energy transition. MITEI has multiple corporate members that have been supporting MIT’s efforts to advance technologies required to harness fusion energy.

An abundance of helium, a destructive force

Key to a fusion reactor is a superheated plasma — an ionized gas — that’s reacting inside a vacuum vessel. As light atoms in the plasma combine to form heavier ones, they release fast neutrons with high kinetic energy that shoot through the surrounding vacuum vessel into a coolant. During this process, those fast neutrons gradually lose their energy by causing radiation damage and generating heat. The heat that’s transferred to the coolant is eventually used to raise steam that drives an electricity-generating turbine. The problem is finding a material for the vacuum vessel that remains strong enough to keep the reacting plasma and the coolant apart, while allowing the fast neutrons to pass through to the coolant. If one considers only the damage due to neutrons knocking atoms out of position in the metal structure, the vacuum vessel should last a full decade. However, depending on what materials are used in the fabrication of the vacuum vessel, some projections indicate that the vacuum vessel will last only six to 12 months. Why is that? Today’s nuclear fission reactors also generate neutrons, and those reactors last far longer than a year. The difference is that fusion neutrons possess much higher kinetic energy than fission neutrons do, and as they penetrate the vacuum vessel walls, some of them interact with the nuclei of atoms in the structural material, giving off particles that rapidly turn into helium atoms. The result is hundreds of times more helium atoms than are present in a fission reactor. Those helium atoms look for somewhere to land — a place with low “embedding energy,” a measure that indicates how much energy it takes for a helium atom to be absorbed. As Li explains, “The helium atoms like to go to places with low helium embedding energy.” And in the metals used in fusion vacuum vessels, there are places with relatively low helium embedding energy — namely, naturally occurring openings called grain boundaries. Metals are made up of individual grains inside which atoms are lined up in an orderly fashion. Where the grains come together there are gaps where the atoms don’t line up as well. That open space has relatively low helium embedding energy, so the helium atoms congregate there. Worse still, helium atoms have a repellent interaction with other atoms, so the helium atoms basically push open the grain boundary. Over time, the opening grows into a continuous crack, and the vacuum vessel breaks. That congregation of helium atoms explains why the structure fails much sooner than expected based just on the number of helium atoms that are present. Li offers an analogy to illustrate. “Babylon is a city of a million people. But the claim is that 100 bad persons can destroy the whole city — if all those bad persons work at the city hall.” The solution? Give those bad persons other, more attractive places to go, ideally in their own villages. To Li, the problem and possible solution are the same in a fusion reactor. If many helium atoms go to the grain boundary at once, they can destroy the metal wall. The solution? Add a small amount of a material that has a helium embedding energy even lower than that of the grain boundary. And over the past two years, Li and his team have demonstrated — both theoretically and experimentally — that their diversionary tactic works. By adding nanoscale particles of a carefully selected second material to the metal wall, they’ve found they can keep the helium atoms that form from congregating in the structurally vulnerable grain boundaries in the metal.

Looking for helium-absorbing compounds

To test their idea, So Yeon Kim ScD ’23 of the Department of Materials Science and Engineering and Haowei Xu PhD ’23 of the Department of Nuclear Science and Engineering acquired a sample composed of two materials, or “phases,” one with a lower helium embedding energy than the other. They and their collaborators then implanted helium ions into the sample at a temperature similar to that in a fusion reactor and watched as bubbles of helium formed. Transmission electron microscope images confirmed that the helium bubbles occurred predominantly in the phase with the lower helium embedding energy. As Li notes, “All the damage is in that phase — evidence that it protected the phase with the higher embedding energy.” Having confirmed their approach, the researchers were ready to  search  for helium-absorbing compounds that would work well with iron, which is often the principal metal in vacuum vessel walls. “But calculating helium embedding energy for all sorts of different materials would be computationally demanding and expensive,” says Kim. “We wanted to find a metric that is easy to compute and a reliable indicator of helium embedding energy.” They found such a metric: the “atomic-scale free volume,” which is basically the maximum size of the internal vacant space available for helium atoms to potentially settle. “This is just the radius of the largest sphere that can fit into a given crystal structure,” explains Kim. “It is a simple calculation.” Examination of a series of possible helium-absorbing ceramic materials confirmed that atomic free volume correlates well with helium embedding energy. Moreover, many of the ceramics they investigated have higher free volume, thus lower embedding energy, than the grain boundaries do. However, in order to identify options for the nuclear fusion application, the screening needed to include some other factors. For example, in addition to the atomic free volume, a good second phase must be mechanically robust (able to sustain a load); it must not get very radioactive with neutron exposure; and it must be compatible — but not too cozy — with the surrounding metal, so it disperses well but does not dissolve into the metal. “We want to disperse the ceramic phase uniformly in the bulk metal to ensure that all grain boundary regions are close to the dispersed ceramic phase so it can provide protection to those regions,” says Li. “The two phases need to coexist, so the ceramic won’t either clump together or totally dissolve in the iron.” Using their analytical tools, Kim and Xu examined about 50,000 compounds and identified 750 potential candidates. Of those, a good option for inclusion in a vacuum vessel wall made mainly of iron was iron silicate.

Experimental testing

The researchers were ready to examine samples in the lab. To make the composite material for proof-of-concept  demonstrations , Kim and collaborators dispersed nanoscale particles of iron silicate into iron and implanted helium into that composite material. She took X-ray diffraction (XRD) images before and after implanting the helium and also computed the XRD patterns. The ratio between the implanted helium and the dispersed iron silicate was carefully controlled to allow a direct comparison between the experimental and computed XRD patterns. The measured XRD intensity changed with the helium implantation exactly as the calculations had predicted. “That agreement confirms that atomic helium is being stored within the bulk lattice of the iron silicate,” says Kim. To follow up, Kim directly counted the number of helium bubbles in the composite. In iron samples without the iron silicate added, grain boundaries were flanked by many helium bubbles. In contrast, in the iron samples with the iron silicate ceramic phase added, helium bubbles were spread throughout the material, with many fewer occurring along the grain boundaries. Thus, the iron silicate had provided sites with low helium-embedding energy that lured the helium atoms away from the grain boundaries, protecting those vulnerable openings and preventing cracks from opening up and causing the vacuum vessel to fail catastrophically. The researchers conclude that adding just 1 percent (by volume) of iron silicate to the iron walls of the vacuum vessel will cut the number of helium bubbles in half and also reduce their diameter by 20 percent — “and having a lot of small bubbles is OK if they’re not in the grain boundaries,” explains Li.

Thus far, Li and his team have gone from computational studies of the problem and a possible solution to experimental demonstrations that confirm their approach. And they’re well on their way to commercial fabrication of components. “We’ve made powders that are compatible with existing commercial 3D printers and are preloaded with helium-absorbing ceramics,” says Li. The helium-absorbing nanoparticles are well dispersed and should provide sufficient helium uptake to protect the vulnerable grain boundaries in the structural metals of the vessel walls. While Li confirms that there’s more scientific and engineering work to be done, he, along with Alexander O’Brien PhD ’23 of the Department of Nuclear Science and Engineering and Kang Pyo So, a former postdoc in the same department, have already developed a startup company that’s ready to 3D print structural materials that can meet all the challenges faced by the vacuum vessel inside a fusion reactor. This research was supported by Eni S.p.A. through the MIT Energy Initiative. Additional support was provided by a Kwajeong Scholarship; the U.S. Department of Energy (DOE) Laboratory Directed Research and Development program at Idaho National Laboratory; U.S. DOE Lawrence Livermore National Laboratory; and Creative Materials Discovery Program through the National Research Foundation of Korea.

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AI assistant monitors teamwork to promote effective collaboration

On a research cruise around Hawaii in 2018, Yuening Zhang SM ’19, PhD ’24 saw how difficult it was to keep a tight ship. The careful coordination required to map underwater terrain could sometimes led to a stressful environment for team members, who might have different understandings of which tasks must be completed in spontaneously changing conditions. During these trips, Zhang considered how a robotic companion could have helped her and her crewmates achieve their goals more efficiently.

Six years later, as a research assistant in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), Zhang developed what could be considered a missing piece: an AI assistant that communicates with team members to align roles and accomplish a common goal. In a paper presented at the International Conference on Robotics and Automation (ICRA) and published on IEEE Xplore on Aug. 8 , she and her colleagues present a system that can oversee a team of both human and AI agents, intervening when needed to potentially increase teamwork effectiveness in domains like search-and-rescue missions, medical procedures, and strategy video games.

The CSAIL-led group has developed a theory of mind model for AI agents, which represents how humans think and understand each other’s possible plan of action when they cooperate in a task. By observing the actions of its fellow agents, this new team coordinator can infer their plans and their understanding of each other from a prior set of beliefs. When their plans are incompatible, the AI helper intervenes by aligning their beliefs about each other, instructing their actions, as well as asking questions when needed.

For example, when a team of rescue workers is out in the field to triage victims, they must make decisions based on their beliefs about each other’s roles and progress. This type of epistemic planning could be improved by CSAIL’s software, which can send messages about what each agent intends to do or has done to ensure task completion and avoid duplicate efforts. In this instance, the AI helper may intervene to communicate that an agent has already proceeded to a certain room, or that none of the agents are covering a certain area with potential victims.

“Our work takes into account the sentiment that ‘I believe that you believe what someone else believes,’” says Zhang, who is now a research scientist at Mobi Systems. “Imagine you’re working on a team and you ask yourself, ‘What exactly is that person doing? What am I going to do? Does he know what I am about to do?’ We model how different team members understand the overarching plan and communicate what they need to accomplish to help complete their team’s overall goal.”

AI to the rescue

Even with a sophisticated plan, both human and robotic agents will encounter confusion and even make mistakes if their roles are unclear. This plight looms especially large in search-and-rescue missions, where the objective may be to locate someone in danger despite limited time and a vast area to scan. Thankfully, communication technology augmented with the new robotic assistant could potentially notify the search parties about what each group is doing and where they’re looking. In turn, the agents could navigate their terrain more efficiently.

This type of task organization could aid in other high-stakes scenarios like surgeries. In these cases, the nurse first needs to bring the patient to the operation room, then the anesthesiologist puts the patient to sleep before the surgeons begin the operation. Throughout the operation, the team must continuously monitor the patient’s condition while dynamically responding to the actions of each colleague. To ensure that each activity within the procedure remains well-organized, the AI team coordinator could oversee and intervene if confusion about any of these tasks arises.

Effective teamwork is also integral to video games like “Valorant,” where players collaboratively coordinate who needs to attack and defend against another team online. In these scenarios, an AI assistant could pop up on the screen to alert individual users about where they’ve misinterpreted which tasks they need to complete.

Before she led the development of this model, Zhang designed EPike, a computational model that can act as a team member. In a 3D simulation program, this algorithm controlled a robotic agent that needed to match a container to the drink chosen by the human. As rational and sophisticated as they may be, cases arise where these AI-simulated bots are limited by their misconceptions about their human partners or the task. The new AI coordinator can correct the agents’ beliefs when needed to resolve potential problems, and it consistently intervened in this instance. The system sent messages to the robot about the human’s true intentions to ensure it matched the container correctly.

“In our work on human-robot collaboration, we’ve been both humbled and inspired over the years by how fluid human partners can be,” says Brian C. Williams, MIT professor of aeronautics and astronautics, CSAIL member, and senior author on the study. “Just look at a young couple with kids, who work together to get their kids breakfast and off to school. If one parent sees their partner serving breakfast and still in their bathrobe, the parent knows to shower quickly and shuffle the kids off to school, without the need to say a word. Good partners are well in tune with the beliefs and goals of each other, and our work on epistemic planning strives to capture this style of reasoning.”

The researchers’ method incorporates probabilistic reasoning with recursive mental modeling of the agents, allowing the AI assistant to make risk-bounded decisions. In addition, they focused on modeling agents’ understanding of plans and actions, which could complement previous work on modeling beliefs about the current world or environment. The AI assistant currently infers agents’ beliefs based on a given prior of possible beliefs, but the MIT group envisions applying machine learning techniques to generate new hypotheses on the fly. To apply this counterpart to real-life tasks, they also aim to consider richer plan representations in their work and reduce computation costs further.

Dynamic Object Language Labs President Paul Robertson, Johns Hopkins University Assistant Professor Tianmin Shu, and former CSAIL affiliate Sungkweon Hong PhD ’23 join Zhang and Williams on the paper. Their work was supported, in part, by the U.S. Defense Advanced Research Projects Agency (DARPA) Artificial Social Intelligence for Successful Teams (ASIST) program.

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Post-MS Doctor of Philosophy (PhD) in Nursing Program - Admissions

The University at Buffalo's Post-Master's Doctor of Philosophy (PhD) in Nursing program is designed to prepare experienced nurses for leadership roles in nursing science and academia. This program equips nurse scholars to advance knowledge development, theory generation, and hypothesis testing to improve nursing practice and health care outcomes. All PhD program tracks are offered online, providing the flexibility needed for working professionals.

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Admissions requirements.

• Equivalent of a Bachelor of Science in nursing (BSN) and Master of Science in nursing (MSN) degree.
• Active U.S. RN license or foreign nursing license.
• Overall MSN GPA of 3.25.

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• Application fee: $75
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Additional requirements for international applicants, all graduate nursing program applicants.

• SPEAK Test , TOEFL or IELTS scores  (minimum scores and more information);  UB TOEFL code: 2925.
• International Credentials/Transcripts/Proof of Degree/Translations. A WES document is strongly preferred. 
• Upon admission to the program, you will be required to submit official transcripts/degrees/translations in a sealed envelope to the International Admission Office.
• Immigration and financial documents.

DNP Program Applicants

• Students applying to the DNP program are not eligible to obtain an F1 student visa.  Visa requirements can be found here . 
• If you do not have a US RN license, you must contact the state board of nursing to apply. 

Application Deadlines

All documents must be received by the deadline.  

Additional Information

Graduate programs information sessions.

Tanner Gelatt Assistant Director of Graduate Recruitment 202 Beck Hall 716-829-3765 [email protected] Schedule a meeting with Tanner.

The University at Buffalo is committed to ensuring equal access to its programs and activities. View UB's Notice of Discrimination here.