phd in machine design

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Doctoral Programs in Computational Science and Engineering

Doctor of philosophy in computational science and engineering, program requirements, programs offered by ccse in conjunction with select departments in the schools of engineering and science.

The interdisciplinary doctoral program in Computational Science and Engineering ( PhD in CSE + Engineering or Science ) offers students the opportunity to specialize at the doctoral level in a computation-related field of their choice via computationally-oriented coursework and a doctoral thesis with a disciplinary focus related to one of eight participating host departments, namely, Aeronautics and Astronautics; Chemical Engineering; Civil and Environmental Engineering; Earth, Atmospheric and Planetary Sciences; Materials Science and Engineering; Mathematics; Mechanical Engineering; or Nuclear Science and Engineering.

Doctoral thesis fields associated with each department are as follows:

• Aerospace Engineering and Computational Science
• Computational Science and Engineering (available only to students who matriculate in 2023–2024 or earlier)
• Chemical Engineering and Computation
• Civil Engineering and Computation
• Environmental Engineering and Computation
• Computational Materials Science and Engineering
• Mechanical Engineering and Computation
• Computational Nuclear Science and Engineering
• Nuclear Engineering and Computation
• Computational Earth, Science and Planetary Sciences
• Mathematics and Computational Science

As with the standalone CSE PhD program, the emphasis of thesis research activities is the development of new computational methods and/or the innovative application of state-of-the-art computational techniques to important problems in engineering and science. In contrast to the standalone PhD program, however, this research is expected to have a strong disciplinary component of interest to the host department.

The interdisciplinary CSE PhD program is administered jointly by CCSE and the host departments. Students must submit an application to the CSE PhD program, indicating the department in which they wish to be hosted. To gain admission, CSE program applicants must receive approval from both the host department graduate admission committee and the CSE graduate admission committee. See the website for more information about the application process, requirements, and relevant deadlines .

Once admitted, doctoral degree candidates are expected to complete the host department's degree requirements (including qualifying exam) with some deviations relating to coursework, thesis committee composition, and thesis submission that are specific to the CSE program and are discussed in more detail on the CSE website . The most notable coursework requirement associated with this CSE degree is a course of study comprising five graduate subjects in CSE (below).

Computational Concentration Subjects

Note: Students may not use more than 12 units of credit from a "meets with undergraduate" subject to fulfill the CSE curriculum requirements

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The PDF includes all information on this page and its related tabs. Subject (course) information includes any changes approved for the current academic year.

Mechanical Engineering

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Systems Design (Ph.D.)

Why pursue a Ph.D. in s ystems d esign at UNH?

The s ystems d esign program at UNH will help you address contemporary engineering and scientific problems that can be solved only through the cooperation of a variety of disciplines. Our interdepartmental program is aimed at developing scientists / engineers with management ability and engineers with system analysis and design capability. You will learn to make creative techni cal contributions to complex and to large-scale systems . You will work closely with a n interdisciplinary guidance committee to develop a course of study that addresses core degree requirements while also being tailored to your specific focus area s . Systems d esign engineers are in high demand in academia, research , industry and management .

Program H ighlights

Our program offers two professional directions : y ou will be able to concentrate on develop ing the skills and technical expertise to work with and direct groups of people on large-scale technical projects , or y ou can build and develop your capabilities in the theory and analysis of large-scale complex systems. You’ll work across varying departments with award-winning researchers , many of whom have received prestigious National Science Foundation CAREER awards. You’ll have access to world-class laboratories including the John Olson Advanced Manufacturing Center, the indoor underwater facilities at the Jere A. Chase Ocean Engineering Laboratory, and the Flow Physics Facility , which houses the largest boundary-layer wind tunnel in the world.

Potential career areas

• B iomedical e ngineering
• Communications
• Environment
• Information technology
• Large- s cale d esign and m anagement
• Machine l earning and i ntelligence
• Policymaking
• Robotics and a utomation
• Transportation

May-Win Thein

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Curriculum & Requirements

Program description.

The systems design doctoral degree is an interdepartmental program that addresses contemporary engineering and scientific problems that can be solved only through the cooperation of a variety of disciplines. Students in systems design can elect one of two professional directions. The first develops professionals with the technical expertise of a Ph.D. and with the ability to work with and direct groups of people working on large-scale technical projects. The second direction develops engineers with capabilities in the theory and analysis of large-scale complex systems. Concentration in an area of specific individual interest is combined with participation in a larger interdisciplinary project.

Requirements for the Program

Degree requirements.

Following entrance into the program, a guidance committee is appointed for the student by the dean of the Graduate School upon recommendation of the student's area coordinator. This committee assists the student in outlining a program and may specify individual coursework requirements in addition to those required by the area of specialization. The committee also conducts an annual in-depth review of each student's progress and, following substantial completion of a student's coursework, administers the qualifying examination. This committee is also responsible for administering the language examination and/or research-­tool proficiency requirements. Coursework and language requirements should normally be completed by the end of the second year of full­-time graduate study and must be completed before the student can be advanced to candidacy. Typically, at least 13 courses beyond the Bachelor of Science degree are required.

Upon the successful completion of the qualifying examination and other proficiency requirements, the student is advanced to candidacy and, upon the recommendation of the student's area coordinator, a doctoral committee is appointed by the dean of the Graduate School. The doctoral committee conducts an annual review of the student's progress, supervises, and approves the doctoral dissertation, and administers the final dissertation defense.

To obtain a Ph.D. degree, a student must meet all of the general requirements as stated under academic regulations and degree requirements of the Graduate School. Students are normally expected to take coursework equivalent to two full-time academic years beyond the baccalaureate and to complete a dissertation on original technical research that will require at least one additional year of full­-time study.

Student Learning Outcomes

• A deep understanding of at least one core area within CEPS.
• A broader understanding of at least 1 other area of CEPS (within the same department or another department) or another college that is/are different from the core area of research and that is/are necessary to complete the student’s multi-disciplinary research.
• Ability to think critically and creatively in defining research questions and to outline strategies of inquiry.
• Ability to combine the knowledge and skills across multiple disciplines to solve a complex and/or large-scale problem.
• Ability to document research outcomes comprehensively for publication.
• Ability to communicate research results to scientific audience in conferences.
• Ability to work collaboratively with other peers.

Application Requirements & Deadlines

Applications must be completed by the following deadlines in order to be reviewed for admission:

• Fall : Feb. 15 (for funding); April 1 (recommended US; final international); July 1 (final)
• Spring : Dec. 1; Nov. 1 for international students
• Summer : N/A
• Special : N/A

Application fee : $65

Campus : Durham

New England Regional : No

Accelerated Masters Eligible : No

New Hampshire Residents

Students claiming in-state residency must also submit a Proof of Residence Form . This form is not required to complete your application, but you will need to submit it after you are offered admission or you will not be able to register for classes.

Transcripts

If you attended UNH or Granite State College (GSC) after September 1, 1991, and have indicated so on your online application, we will retrieve your transcript internally; this includes UNH-Durham, UNH-Manchester, UNH Non-Degree work and GSC. 

If you did not attend UNH, or attended prior to September 1, 1991, then you must upload a copy (PDF) of your transcript in the application form. International transcripts must be translated into English.

If admitted , you must then request an official transcript be sent directly to our office from the Registrar's Office of each college/university attended. We accept transcripts both electronically and in hard copy:

• Electronic Transcripts : Please have your institution send the transcript directly to [email protected] . Please note that we can only accept copies sent directly from the institution.
• Paper Transcripts : Please send hard copies of transcripts to: UNH Graduate School, Thompson Hall- 105 Main Street, Durham, NH 03824. You may request transcripts be sent to us directly from the institution or you may send them yourself as long as they remain sealed in the original university envelope.

Transcripts from all previous post-secondary institutions must be submitted and applicants must disclose any previous academic or disciplinary sanctions that resulted in their temporary or permanent separation from a previous post-secondary institution. If it is found that previous academic or disciplinary separations were not disclosed, applicants may face denial and admitted students may face dismissal from their academic program.

Letters of recommendation: 3 required

Recommendation letters submitted by relatives or friends, as well as letters older than one year, will not be accepted.

Test Scores: GRE Required

GRE required. Request official test scores to be sent directly to the Graduate School by the testing service. Test scores more than five years old are not acceptable. Student copies and photo copies of scores are not considered official. Our CEEB code is 3918.

For general information about test scores, including waiver requests and current COVID related impacts,  please visit our Test Scores webpage .

Personal Statement/Essay Questions

Prepare a brief but careful statement regarding:

• Reasons you wish to do graduate work in this field, including your immediate and long-range objectives.
• Your specific research or professional interest and experiences in this field.

Important Notes

All applicants are encouraged to contact programs directly to discuss program-specific application questions.

International Applicants

Prospective international students are required to submit TOEFL, IELTS, or equivalent examination scores. English Language Exams may be waived if English is your first language. If you wish to request a waiver, then please visit our Test Scores webpage for more information.

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Faculty directory.

See: https://ceps.unh.edu/mechanical-engineering/faculty-staff-directory

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Design & Manufacturing - Mechanical Engineering - Purdue University

Design & Manufacturing    

If you want to build it, first you’ve got to design it. That’s why Design & Manufacturing is such a vital aspect of engineering research at Purdue, discovering the ideals for mechanical systems, computational models, and human ergonomics.

Human beings and machines are interacting in new and unique ways in the 21st century. In one Purdue lab, researchers use toys and video games as a vehicle to study how humans utilize creativity in the smartphone era.  In another, faculty are studying materials at the nanoscopic level, to determine how best to manufacture the nanomaterials of the future.  Another lab compares traditional manufacturing techniques with open-source culture, mapping out new paradigms for social and technical systems.

Design also collaborates with and strengthens other areas of engineering, like biomechanics, robotics, manufacturing, and vehicles.

Purdue collaborates with Navajo Tech on manufacturing research

Purdue and collaborators 'put a flag in the ground' for in-space manufacturing

Purdue team wins "blue sky" award for the future of manufactured meat

Designing 3D food printers with frugal engineering

Purdue teams up with 3M to produce PPE

Sticktronics: Sometimes it's good to be thin-skinned

Shape Structuralizer streamlines the making process

Stacking chips to bring higher-performance computing

Toy Fair showcases Boilermaker fun

Faculty in Design & Manufacturing

Andres arrieta.

• Adaptive structures
• Mechanical metamaterials
• Robotic materials
• Programmable structures
• Multistable structures
• Structural nonlinearity
• Elastic instabilities
• Structural dynamics
• Nonlinear vibrations

Shubhra Bansal

• Renewable Energy Materials (physics-based energy yield predictions, sustainable PV and energy storage materials, recycling)
• Electro-Optical-Thermo-Mechanical Reliability (in-situ and in-operando accelerated stress tests)
• Heterogeneous Integration & Advanced Packaging (sub-10 μm pitch interconnects, low-loss interposers)
• Harsh Environment Electronics Integration (high temperature Pb-free solders and nano-thermal interfaces)

Ilias Bilionis

• Uncertainty propagation
• Inverse problems
• Propagation of information across scales
• Optimal learning
• Materials by design

Laura Blumenschein

• Growing robots
• Soft robotics
• Bioinspired systems
• Wearable robots
• Soft matter

Adrian Buganza Tepole

• Predictive computational tools for biological adaptation processes
• Tissue expansion
• Wound healing
• Reconstructive surgery optimization
• Numerical methods for biological membranes

Mukerrem Cakmak

• Modeling and experimental studies on processing
• Structure property relationships in polymer films and moldings and polymer/metal/ceramic hybrid systems

David Cappelleri

• Multi-scale robotic manipulation and assembly
• Mobile micro/nano robotics
• Micro/nano aerial vehicles
• Micro-Bio robotics
• Mechatronics
• Automation for the life sciences

George Chiu

• Dynamic systems and control
• Digital and functional printing and fabrication
• Motion and vibration control and perception
• Embedded systems and real-time control

Alex Chortos

• Bio-inspired and mechanically adaptive electronics
• Multimaterial additive fabrication
• Soft actuators (artificial muscles)
• Wearable actuators (haptics)
• Polymer design and polymer physics
• Deformation sensors and transistors

Raymond Cipra

• Mechanical systems design
• Analysis and simulation
• Computer aided engineering
• Robotics and automation

Hamid Dalir

• Composites materials design and manufacturing
• Sustainable and recyclable-by-design polymers and composites
• Polymer processing and characterization
• Composites recycling
• Hybrid manufacturing systems
• Multiscale modeling
• Damage mechanics

Greg Jensen

James Jones

• Cooperative learning
• Active noise and vibration control
• Smart materials
• Intelligent structures

Klod Kokini

• Thermal stresses, thermal fracture and fatigue of advanced materials, in particular high temperature materials, ceramic coatings.
• Mechanical behavior, design and remodeling of biological tissues, effect of stresses on remodeling, microbiomechanics of cell-extracellular matrix (ECM) interactions, tissue engineering

Chi Hwan Lee

• Wearable biomedical devices
• 'Crack’-driven transfer printing technology
• Scalable manufacturing technology
• Mechanics and materials for flexible/stretchable electronics

Heather Liddell

• Sustainable manufacturing
• Environmental life cycle assessment
• Mechanics of multilayered systems
• Adhesion in paints and coatings
• Lightweighting strategies for transportation

Nina Mahmoudian

• Marine Robotics
• Unmanned Systems
• Energy Autonomy
• Systems Design
• Coordination and Controls

Ajay Malshe

• Bio-inspired designs
• Surface engineering and multifunctional materials
• Convergent Manufacturing for Industry 5.0: hybrid manufacturing processes, heterogeneous materials, and bio-inspired designs
• Systems integration, productization, and production
• Heavy-duty machines: machining, lubrication, and corrosion
• Heterogeneous and hierarchical integration (mechanical-electrical-optical and nano-micro-meso-macro)
• Precision agricultural and food: cellular agriculture, vertical farming, micro-production, and resilience
• Frugal engineering, social innovations, and social equity
• Manufacturing in space

Jitesh Panchal

• Computational Design of Socio-Technical Systems
• Secure Design and Manufacturing
• Engineering Design by Self-Organized Virtual Communities
• Integrated Products and Materials Design

Gordon Pennock

• Kinematic synthesis and analysis
• Multi-degree-of-freedom mechanisms

Karthik Ramani

• Human Skill and Augmentation
• Collaborative and Hybridized Intelligence
• Deep Learning of Shapes and Computer Vision
• Human-Robot-Machine Interactions
• Making to Manufacturing (M2M)
• Factory of the Future and Robotics
• Manufacturing Productivity

Farshid Sadeghi

• Contact mechanics
• Stresses, fatigue and friction of rolling/sliding
• Micro-mechanics of boundary and mixed lubrication regimes
• Spall initiation and propagation
• Surface science and damage
• Dynamics of ball and rolling element bearings and rotating systems
• Friction induced vibration and squeal in dry contacts
• Friction and wear of dry and lubricated contacts
• Virtual tribology
• Dry and lubricated fretting wear
• MEMS for in-situ monitoring of tribological contacts
• Discrete element modeling

• Multi-process/multi-material additive manufacturing
• Nondestructive evaluation
• Advanced acoustic materials and metamaterials
• Ultrasonics

Ganesh Subbarayan

• Computational and experimental solid mechanics focused on fatigue, fracture, and multi-physics phase evolution problems
• Computational techniques including Finite Element Analysis (FEA), Isogeometric Analysis (IGA), geometric modeling, CAD and optimal design
• Heterogeneous Integration and Advanced Electronics Packaging with a focus on thermomechanical behavior, reliability, and electrical-thermal-mechanical co-design

• Multiscale superfast 3D optical sensing
• Biophotonic imaging
• Optical metrology
• Machine/computer vision
• 3D video telepresence
• 3D video processing
• Virtual reality
• Human computer interaction

• Environment friendly design and life cycle engineering
• Applications of bio-based materials in manufacturing
• Fast and low-cost detection of pathogenic microorganisms
• Biomass thermo-chemical upgrading for liquid and gaseous fuel

• Deformation, stress, plasticity, fracture
• Multiscale modeling, first-principles, molecular dynamics simulations, and finite element modeling
• In-situ experiments
• Mechanics of redox active materials - Li-ion batteries, Na-ion batteries, all-solid-state batteries
• Mechanics of polymeric materials - organic electrochromics, superelastic organic semiconductors

I want to research in these fundamental areas...

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PhD Machines and Equipment Design

Programme details.

The doctoral study programme Machines and Equipment Design is focused on independent scientific and research projects in the field of the design of machines and equipment. Its aim is to produce highly-educated and creative graduates capable of taking part in scientific, research, and professional activities. The Ph.D. candidates further extend and refine their knowledge of mathematics, physics, and applied sciences in the theoretical foundation of the study discipline to be able to succeed in solutions of tasks in the fields of development and design, modelling and simulations of operations and design and performance of experiments.

The graduates are able to independently apply the mastered skills and the high level of theoretical knowledge provided in lectures and acquired through modern learning methods, e. g. calculations and experiments, for solving specific problems in the selected areas of the design of parts and mechanisms of machines, wheeled transport, handling machines, working and assembling machines, piston combustion engines, glass-making machines and robotics, textile machines and machines for the production of nanofibres, equipment for thermal technologies and for technical diagnostics, etc. Furthermore, they are familiar with the research methods in the field of the design of machines and equipment and capable of critical analysis, evaluation, and synthesis, thus able to discuss the results of their investigations and to extend the sum of the current knowledge in a professional way worth of publishing and sharing with other members of the professional community both in their country and abroad.

After the completion of the study programme the graduates will succeed in positions of research team members in both theoretical and applied research areas or as experts in the teams of industrial development centers and major research institutions focusing on a particular area. Due to their profound knowledge and professional approaches, they will also succeed in a broader context as lecturers of tertiary education institutions.

More detailed information on the faculty website

Škoda Auto PhD Programme

PhD candidates at TUL are eligible to apply for participation in the Škoda Auto PhD programme or they can write their thesis on a topic offered by the company.

Doctoral studies at KTH

Complete a doctoral degree (PhD) in a dynamic, international research environment with world-class facilities and close collaboration with industry and prominent universities worldwide.

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KTH Royal Institute of Technology

KTH is Sweden's largest and most respected technical university—ranked top 100 in the 2022 QS World University Rankings. By choosing KTH, you gain access to a vibrant student life and a prestigious academic environment.

As one of our 2,000 doctoral students, you will take courses and devote yourself to a research project under the supervision of an experienced researcher. Most students are employed and receive a monthly salary. Begin your journey towards a KTH degree today. 

Explore how doctoral studies work at KTH and if we are a good fit for you. 

Want to join us?

We have gathered all the steps you need to take to become a doctoral student.

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Machine Learning (Ph.D.)

The curriculum for the PhD in Machine Learning is truly multidisciplinary, containing courses taught in eight schools across three colleges at Georgia Tech: the Schools of Computational Science and Engineering, Computer Science, and Interactive Computing in the College of Computing; the Schools of Industrial and Systems Engineering, Electrical and Computer Engineering, and Biomedical Engineering in the College of Engineering; and the School of Mathematics in the College of Science.

+86 10 8639 1449 | [email protected]

PhD in  Machine Design and Theory

Introduction to the program.

The PhD in Machine Design and Theory   is a 3 year program taught in English to international students. Students can start the program in September each year.

About WHU - Wuhan University

Entry Requirements

Application deadline, tuition fees, application process.

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Smart. Open. Grounded. Inventive. Read our Ideas Made to Matter.

Which program is right for you?

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

A rigorous, hands-on program that prepares adaptive problem solvers for premier finance careers.

A 12-month program focused on applying the tools of modern data science, optimization and machine learning to solve real-world business problems.

Earn your MBA and SM in engineering with this transformative two-year program.

Combine an international MBA with a deep dive into management science. A special opportunity for partner and affiliate schools only.

A doctoral program that produces outstanding scholars who are leading in their fields of research.

Bring a business perspective to your technical and quantitative expertise with a bachelor’s degree in management, business analytics, or finance.

A joint program for mid-career professionals that integrates engineering and systems thinking. Earn your master’s degree in engineering and management.

An interdisciplinary program that combines engineering, management, and design, leading to a master’s degree in engineering and management.

Executive Programs

A full-time MBA program for mid-career leaders eager to dedicate one year of discovery for a lifetime of impact.

This 20-month MBA program equips experienced executives to enhance their impact on their organizations and the world.

Non-degree programs for senior executives and high-potential managers.

A non-degree, customizable program for mid-career professionals.

PhD Program

Program overview.

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Rigorous, discipline-based research is the hallmark of the MIT Sloan PhD Program. The program is committed to educating scholars who will lead in their fields of research—those with outstanding intellectual skills who will carry forward productive research on the complex organizational, financial, and technological issues that characterize an increasingly competitive and challenging business world.

Start here.

Learn more about the program, how to apply, and find answers to common questions.

Admissions Events

Check out our event schedule, and learn when you can chat with us in person or online.

Start Your Application

Visit this section to find important admissions deadlines, along with a link to our application.

Click here for answers to many of the most frequently asked questions.

PhD studies at MIT Sloan are intense and individual in nature, demanding a great deal of time, initiative, and discipline from every candidate. But the rewards of such rigor are tremendous:  MIT Sloan PhD graduates go on to teach and conduct research at the world's most prestigious universities.

PhD Program curriculum at MIT Sloan is organized under the following three academic areas: Behavior & Policy Sciences; Economics, Finance & Accounting; and Management Science. Our nine research groups correspond with one of the academic areas, as noted below.

MIT Sloan PhD Research Groups

Behavioral & policy sciences.

Economic Sociology

Institute for Work & Employment Research

Organization Studies

Technological Innovation, Entrepreneurship & Strategic Management

Economics, Finance & Accounting

Accounting  

Management Science

Information Technology

System Dynamics  

Those interested in a PhD in Operations Research should visit the Operations Research Center .  

PhD Program Structure

Additional information including coursework and thesis requirements.

MIT Sloan Predoctoral Opportunities

MIT Sloan is eager to provide a diverse group of talented students with early-career exposure to research techniques as well as support in considering research career paths.

Rising Scholars Conference

The fourth annual Rising Scholars Conference on October 25 and 26 gathers diverse PhD students from across the country to present their research.

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The goal of the MIT Sloan PhD Program's admissions process is to select a small number of people who are most likely to successfully complete our rigorous and demanding program and then thrive in academic research careers. The admission selection process is highly competitive; we aim for a class size of nineteen students, admitted from a pool of hundreds of applicants.

What We Seek

• Outstanding intellectual ability
• Excellent academic records
• Previous work in disciplines related to the intended area of concentration
• Strong commitment to a career in research

MIT Sloan PhD Program Admissions Requirements Common Questions

Dates and Deadlines

Admissions for 2024 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

Students in good academic standing in our program receive a funding package that includes tuition, medical insurance, and a fellowship stipend and/or TA/RA salary. We also provide a new laptop computer and a conference travel/research budget.

Funding Information

Throughout the year, we organize events that give you a chance to learn more about the program and determine if a PhD in Management is right for you.

PhD Program Events

May phd program overview.

During this webinar, you will hear from the PhD Program team and have the chance to ask questions about the application and admissions process.

June PhD Program Overview

July phd program overview, august phd program overview.

Complete PhD Admissions Event Calendar

Unlike formulaic approaches to training scholars, the PhD Program at MIT Sloan allows students to choose their own adventure and develop a unique scholarly identity. This can be daunting, but students are given a wide range of support along the way - most notably having access to world class faculty and coursework both at MIT and in the broader academic community around Boston.

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Profiles of our current students

MIT Sloan produces top-notch PhDs in management. Immersed in MIT Sloan's distinctive culture, upcoming graduates are poised to innovate in management research and education.

Academic Job Market

Doctoral candidates on the current academic market

Academic Placements

Graduates of the MIT Sloan PhD Program are researching and teaching at top schools around the world.

view recent placements 

MIT Sloan Experience

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The PhD Program is integral to the research of MIT Sloan's world-class faculty. With a reputation as risk-takers who are unafraid to embrace the unconventional, they are engaged in exciting disciplinary and interdisciplinary research that often includes PhD students as key team members.

Research centers across MIT Sloan and MIT provide a rich setting for collaboration and exploration. In addition to exposure to the faculty, PhD students also learn from one another in a creative, supportive research community.

Throughout MIT Sloan's history, our professors have devised theories and fields of study that have had a profound impact on management theory and practice.

From Douglas McGregor's Theory X/Theory Y distinction to Nobel-recognized breakthroughs in finance by Franco Modigliani and in option pricing by Robert Merton and Myron Scholes, MIT Sloan's faculty have been unmatched innovators.

This legacy of innovative thinking and dedication to research impacts every faculty member and filters down to the students who work beside them.

Faculty Links

• Accounting Faculty
• Economic Sociology Faculty
• Finance Faculty
• Information Technology Faculty
• Institute for Work and Employment Research (IWER) Faculty
• Marketing Faculty
• Organization Studies Faculty
• System Dynamics Faculty
• Technological Innovation, Entrepreneurship, and Strategic Management (TIES) Faculty

Student Research

“MIT Sloan PhD training is a transformative experience. The heart of the process is the student’s transition from being a consumer of knowledge to being a producer of knowledge. This involves learning to ask precise, tractable questions and addressing them with creativity and rigor. Hard work is required, but the reward is the incomparable exhilaration one feels from having solved a puzzle that had bedeviled the sharpest minds in the world!” -Ezra Zuckerman Sivan Alvin J. Siteman (1948) Professor of Entrepreneurship

Sample Dissertation Abstracts - These sample Dissertation Abstracts provide examples of the work that our students have chosen to study while in the MIT Sloan PhD Program.

We believe that our doctoral program is the heart of MIT Sloan's research community and that it develops some of the best management researchers in the world. At our annual Doctoral Research Forum, we celebrate the great research that our doctoral students do, and the research community that supports that development process.

The videos of their presentations below showcase the work of our students and will give you insight into the topics they choose to research in the program.

How Should We Measure the Digital Economy?

2020 PhD Doctoral Research Forum Winner - Avinash Collis

Watch more MIT Sloan PhD Program  Doctoral Forum Videos

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Faculty Directory

Meet our faculty.

College of Computing

Ph.d. in machine learning, about the curriculum.

The central goal of the Ph.D. program is to train students to perform original, independent research. The most important part of the curriculum is the successful defense of a Ph.D. dissertation, which demonstrates this research ability.

The curriculum is designed with the following principal educational goals:

•    Students will develop a solid understanding of fundamental principles across a range of core areas in the machine learning discipline. •    Students will develop a deep understanding and set of skills and expertise in a specific theoretical aspect or application area of the machine learning discipline. •    The students will be able to apply and integrate the knowledge and skills they have developed and demonstrate their expertise and proficiency in an application area of practical importance. •    Students will be able to engage in multidisciplinary activities by being able to communicate complex ideas in their area of expertise to individuals in other fields, be able to understand complex ideas and concepts from other disciplines, and be able to incorporate these concepts into their own work. The curriculum for the Ph.D. in Machine Learning is truly multidisciplinary, containing courses taught in eight schools across three colleges at Georgia Tech:  •    Computer Science (Computing) •    Computational Science and Engineering (Computing) •    Interactive Computing (Computing) – see Computer Science •     Aerospace Engineering (Engineering) •     Biomedical Engineering (Engineering) •     Electrical and Computer Engineering (Engineering) •     Industrial Systems Engineering (Engineering) •     Mathematics (Sciences) Students must complete four core courses, five electives, a qualifying exam, and a doctoral dissertation defense. All doctorate students are advised by ML Ph.D. Program Faculty . All coursework must be completed before the Ph.D. proposal. An overall GPA of 3.0 is required for the Ph.D. coursework.

Research Opportunities

Our faculty comes from all six colleges across Georgia Tech’s campus, creating many interdisciplinary research opportunities for our students. Our labs focus on research areas such as artificial intelligence, data science, computer vision, natural language processing, optimization, machine learning theory, forecasting, robotics, computational biology, fintech, and more.

External applications are only accepted for the Fall semester each year. The application deadline varies by home school. 

The Machine Learning Ph.D. admissions process works bottom-up through the home schools. Admissions decisions are made by the home school, and then submitted to the Machine Learning Faculty Advisory Committee (FAC) for final approval. Support for incoming students (including guarantees of teaching assistantships and/or fellowships) is determined by the home schools. 

After the admissions have been approved by the FAC, the home school will communicate the acceptance to the prospective student. The home school will also communicate all rejections.

Get to Know Current ML@GT Students

Learn more about our current students, their interests inside and outside of the lab, favorite study spots, and more.

Career Outlook

The machine learning doctorate degree prepares students for a variety of positions in industry, government, and academia. These positions include research, development, product managers, and entrepreneurs. 

Graduates are well prepared for position in industry in areas such as internet companies, robotic and manufacturing companies and financial engineering, to mention a few. Positions in government and with government contractors in software and systems are also possible career paths for program graduates. Graduates are also well-suited for positions in academia involving research and education in departments concerned with the development and application of data-driven models in engineering, the sciences, and computing. 

Frequently Asked Questions

For additional questions regarding the ML Ph.D. program, please take a look at our frequently asked questions.

You can also view the ML Handbook which has detailed information on the program and requirements.

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• CORRESPONDENCE
• 02 April 2024

How can we make PhD training fit for the modern world? Broaden its philosophical foundations

• Ganesh Alagarasan 0

Indian Institute of Science Education and Research, Tirupati, India.

You can also search for this author in PubMed   Google Scholar

You have highlighted how PhD training assessment has stagnated, despite evolving educational methodologies (see Nature 613 , 414 (2023) and Nature 627 , 244; 2024 ). In particular, you note the mismatch between the current PhD journey and the multifaceted demands of modern research and societal challenges.

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Nature 628 , 36 (2024)

doi: https://doi.org/10.1038/d41586-024-00969-x

Competing Interests

The author declares no competing interests.

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