Skyline view of Duke Chapel at sunrise.

PhD—Doctoral Study

Rigorous advanced training in Mechanical Engineering and Materials Science with personalized mentorship from faculty research leaders

The Duke Difference

  • World-class research with global impact in energy, automation, and health care
  • Uniquely interdisciplinary environment—MEMS faculty and students work closely with collaborators within Duke's Trinity College of Arts & Sciences, School of Medicine, and Nicholas School of the Environment, as well as with national and international collaborators at universities, in industry, and at national labs
  • Financial support—Duke MEMS is committed to providing tuition, stipend, and health insurance for all PhD students. Also, MEMS provides travel and registration funds to support your participation in national and international conferences
  • Internships—MEMS PhD students are encouraged to work with their advisors to explore industry internships. Course credit is available
  • Engineering in Service to Society Fellowships—Through the generous support of the Lord Foundation, Duke MEMS PhD students can apply for funds to spend a semester gaining experience in the policy or nonprofit sector (international, national, or local). A number of national policy positions are available near campus
  • Specialization with integrated coursework and research
  • A broad mentoring network that includes your PhD advisor and an interdisciplinary mentoring team.
  • Great location in a city known for tech, entrepreneurship and quality of life—Durham, N.C., is a vibrant city with both nationally-known restaurants and the large Eno River State Park for nearby hiking. Along with Chapel Hill (UNC) and Raleigh (NC State), it forms the Research Triangle region, which together are ranked #6 in Best Place to Live in the U.S. by U.S.News. 
  • Excellent career outcomes—About 45% of our PhD students go on to academic careers, 55% go on to leadership in the public and private sectors.
  •  #10
    national university
  • #25
    Mechanical engineering graduate program
  •  $12
    million in new faculty research awards
  •  39
    Regular rank faculty

Sources: U.S. News, Academic Analytics, Duke University

World-Class Research

Those considering a PhD in mechanical engineering and materials science should be passionate about research. We provide opportunities for students to publish with their faculty advisor, to present research at professional conferences, and to explore their field in a highly collaborative, cross-disciplinary working environment.

Duke MEMS Research Groups, Centers and Initiatives

Our faculty lead research groups, centers and initiatives with strong collaborations in academia and industry.

Research Groups

Research at Duke MEMS addresses fundamental and applied problems, with particular strength in aerospace engineering, dynamics, controls & robotics, materials science & biomaterials, mechanics, design & computing, thermal fluids & energy.

Browse Duke MEMS faculty profiles »

Research Centers

Duke Center for Autonomous Materials Design

The base for teams across 15-plus institutions with the mission of creating stronger materials with tunable properties. The center shares the largest database for inorganic materials at aflow.org.

Duke Robotics

A cross-disciplinary association of labs and faculty spanning Computer Science, Electrical & Computer Engineering and Duke MEMS.

More about Duke Robotics »

Fitzpatrick Institute for Photonics (FIP)

For nearly 25 years, FIP has provided a world-class educational and research environment that trains engineers to make original contributions across the range of light-based technologies.

More about the Fitzpatrick Institute for Photonics »

GUIde Consortium for Aeroelasticity

A turbomachinery aeroelasticity research consortium of government, university and industry partners (GUI). 

More about the GUIde Consortium for Aeroelasticity »

HybriD3

Accelerates the design, discovery and dissemination (D3) of new crystalline organic-inorganic hybrid semiconductors at three neighboring universities: Duke, UNC-Chapel Hill and NC State University. 

More about HybridD3 »

Duke Soft Matter Center

An interdisciplinary effort to create an intellectual climate at Duke based on a common language of soft matter. Facilitates collaboration among faculty in engineering, the natural sciences and medicine. 

More about the Duke Soft Matter Center »

Research Initiatives

Duke Materials Initiative

A Duke-wide community of eight academic departments that facilitate collaboration, research, and education in materials science. 

More about the Duke Materials Initiative »

Duke Energy Initiative

A Duke-wide research collaboration focused on advancing accessible, affordable, reliable, and clean energy. 

More about the Duke Energy Initiative »

PhD Student Research-Study Tracks

As an integrated department in both Mechanical Engineering and Materials Science, Duke MEMS offers multiple, rigorous yet flexible pathways to a PhD with focus in Mechanical Engineering or Materials Science, or a blended and custom combination.

Below, browse course options for the focused curricular tracks: 

Mechanical Engineering Tracks

Aerospace Engineering

Six courses from the following three areas, with at least one in each

Structures and Dynamics

  • ME 541: Intermediate Dynamics
  • ME 544: Advanced Mechanical Vibrations
  • ME 527: Buckling

Aerodynamics, Acoustics, and Fluid Mechanics

  • ME 532: Convective Heat Transfer
  • ME 536: Compressible Flow
  • ME 571: Aerodynamics
  • ME 572: Engineering Acoustics
  • ME 672: Unsteady Aerodynamics
  • ME 775: Aeroelasticity

Mathematical and Computational Methods

NOTE: no more than two can be applied

  • CS 520: Numerical Analysis
  • ME 524: Introduction to the Finite Element Method
  • MATH 551: Applied Partial Differential Equations
  • MATH 575: Mathematical Fluid Dynamics
  • MATH 577: Mathematical Modeling
  • ME 639: Computational Fluid Dynamics and Heat Transfer 
Biomechanical Engineering

Six courses from the following three areas, with at least one in each

Math and Computational Methods

  • ME 524: Introduction to the Finite Element Method
  • ME 525: Nonlinear Finite Element Analysis
  • MATH 551: Applied Partial Differential Equations
  • MATH 575: Mathematical Fluid Dynamics
  • MATH 577: Mathematical Modeling

Mechanics and Fluids

  • BME 528: Biofluid Mechanics
  • CE 541: Structural Dynamics
  • ME 555: Intro to Rheology
  • ME 572: Engineering Acoustics

Biology and Medicine

  • ME 513: Nanobiomechanics
  • BME 527: Cell Mechanics and Mechanotransduction
  • ME 535: Biomedical Microsystems
  • ME 555: Fundamentals of Shock-Wave Lithotripsy
  • ME 555: Systems Engineering
  • ME 555: Experimental Microfluidics
  • ME 711: Nanotechnology Materials Laboratory
Computational Mechanics & Scientific Computing

Six courses in the following areas, with at least one course in each

Applied Math

  • MATH 541: Applied Stochastic Processes
  • MATH 551: Applied Partial Differential Equations
  • MATH 561: Numerical Linear Algebra
  • MATH 577: Mathematical Modeling

Numerical Methods

  • ME 511: Computational Materials Science
  • ME 524: Finite Element Method
  • ME 525: Nonlinear Finite Elements
  • ME 555: Numerical Optimization

Engineering Sciences and Mechanics

  • CEE 520: Continuum Mechanics
  • ME 531: Thermodynamics
  • ME 631: Intermediate Fluid Dynamics

Computer Science/Programming

  • ECE 551D: Programming in C++
  • ME 555: Introduction to Programming
  • CS 570: Artificial Intelligence
  • CS 571D: Probabilistic Machine Learning
Dynamics, Robotics & Controls

Six courses from the following three areas, with at least one in each

Math and Statistics

  • ME 555: Numerical Optimization
  • MATH 561: Numerical Linear Algebra
  • MATH 577: Mathematical Modeling
  • ECE 586: Vector Space Methods
  • BA 911: Convex Optimization

Dynamics and Controls

  • ME 541: Intermediate Dynamics
  • ME 544: Advanced Mechanical Vibrations
  • ME 555: Model Predictive Control
  • ME 627: Linear System Theory
  • ME 742: Nonlinear Mechanical Vibrations

Computational Methods

  • CS 527: Computer Vision
  • ECE 551D: Programming in C++
  • ME 555: Introduction to Programming
  • ME 555: Introduction to Scientific Computing
  • CS 570: Artificial Intelligence
  • CS 571D: Probabilistic Machine Learning
Thermal Fluids & Energy

Six courses from the following three areas, with at least one in each

Energy

  • ME 531 Engineering Thermodynamics
  • ME 532 Convective Heat Transfer
  • ME 555 Carbon Capture and Utilization 
     

Fluids

  • ME 536 Compressible Fluid Flow
  • ME 555 Intro to Rheology
  • ME 572 Engineering Acoustics
  • ME 631 Intermediate Fluid Dynamics

Applied Math and Numerical Methods

  • MATH 551: Applied Partial Differential Equations
  • ME 524: Finite Element Method
  • ME 639 Computational Fluid Dynamics and Heat Transfer

Materials Science Tracks

General Materials Science

One solid-state course from the following

  • CHEM 548: Solid-State/Materials Chemistry
  • ECE 524: Introduction to Solid-State Physics
  • PHYS 516: Quantum Materials
  • ME 555: Modern Materials

One statistical thermodynamics course from the following

  • CHEM 544 Statistical Mechanics
  • PHYS 563 Introduction to Statistical Mechanics
  • PHYS 763 Statistical Mechanics

One quantum mechanics course

  • ECE 521: Quantum Mechanics, or
  • Other graduate-level quantum mechanics course

Two courses from the following

  • ME 555: Materials Synthesis and Processing
  • ME 518: Diffraction and Spectroscopy
  • ME 511: Computational Materials Science
  • ME 555: Molecular Modeling of Soft Materials
  • ME 555: Intro to Rheology
  • ME 555: Carbon Capture and Utilization 
  • ME 711: Nanotechnology Materials Lab

One course from the following

  • ME 516: Thin-Film Photovoltaics
  • ME 515: Introduction to Electronic Materials
  • ME 514: Theoretical and Applied Polymer Science
  • ECE 511: Foundations of Nanoscale Science and Technology
Soft Matter

One "hard matter" course from the following

  • CHEM 548: Solid-State/Materials Chemistry
  • ECE 524: Introduction to Solid-State Physics
  • PHYS 516 Quantum Materials
  • ME 555: Modern Materials

One statistical thermodynamics course from the following

  • CHEM 544 Statistical Mechanics
  • PHYS 563 Introduction to Statistical Mechanics
  • PHYS 763 Statistical Mechanics
  • ME 555: Fundamentals of Soft Matter

Two polymer courses from the following

  • ME 555: Introduction to Polymer Physics
  • ME 514: Theoretical and Applied Polymer Science
  • CHEM 590: Polymer Synthesis
  • ME 555: Intermediate Polymer Physics
  • ME 555: Intro to Rheology

One course from the following

  • ME 555: Molecular Modeling of Soft Materials
  • ME 511: Computational Materials Science
  • ECE 721/ME 711: Nanotechnology Materials Lab/Advanced Lab Materials
  • PHYS 760: Mathematical Methods in Physics
  • MATH 577(229): Mathematical Modeling
AI + Materials

Materials Courses

  • CEE 520: Continuum Mechanics
  • CEE 521: Elasticity
  • CHEM 548: Solid-State/Materials Chemistry
  • CHEM 590: Polymer Synthesis
  • ECE 524: Introduction to Solid-State Physics
  • ECE 511: Foundations of Nanoscale Science & Technology
  • ME 511: Computational Materials Science
  • ME 514: Theoretical and Applied Polymer Science
  • ME 510: Diffraction and Spectroscopy
  • ME 515: Electronic Materials
  • ME 555 (ME 512): Modern Materials
  • ME 555 (562): Materials Synthesis and Processing
  • ME 555 (ME 519): Molecular Modeling of Soft Materials
  • ME 555 (ME 563:) Fundamentals of Soft Matter
  • ME 555 (ME 564): Introduction to Polymer Physics
  • ME 555: Intermediate Polymer Physics
  • ME 555: Intro to Rheology
  • ME 711: Nanotechnology Materials Lab
  • PHYS 516: Quantum Materials

Computational Courses

  • CS 570: Artificial Intelligence
  • CS 671D: Theory and Algorithms for Machine Learning
  • CEE 690: Data Science and ML for CEE
  • ECE 580: Introduction to Machine Learning
  • ECE 590: Deep Learning
  • ECE 682D: Probabilistic Machine Learning
  • CEE 690: Uncertainty Quantification in Computational Science and Engineering
  • ME 511: Computational Materials Science
  • ME 524: Introduction to the Finite Element Method
  • ME 525: Nonlinear Finite Element Analysis
  • ME 555: Numerical Optimization
  • ME (ME 519): Molecular Modeling of Soft Materials

AI and Materials Integrated Courses

  • ME 555: Data and Materials Science Applications
  • ME 555: Sci Computing, Simulation and ML
Amy King

"What I really like about Duke is that it has all the advantages of a big school but within Duke MEMS it feels like a small school. There's really a great sense of community."

Amy King, PhD '20 | Northrop Grumman

A Personal Mentoring Team

A broad mentoring network is a hallmark of the Duke MEMS PhD experience. We believe in creating a highly interdisciplinary research community.

PhD students work closely with a research advisor. In addition, we help you form a personal Mentoring Team that includes a faculty member outside of your research area and senior PhD students.

Authentic Opportunities to Learn Mentorship Through Mentoring

In preparation for your role as a research mentor, Duke Engineering actively encourages and supports efforts by its PhD students to mentor undergraduates in research work.

Our PhD students can register to serve as a mentor and post a research project to a university-wide directory of research opportunities for undergraduates: Muser.

As mentors, our PhD students build professional mentoring relationships with undergraduates, while increasing undergraduate involvement in research—one of the hallmarks of a Duke Engineering education.

A Welcoming, Inclusive Community

By choosing Duke, you join an engaged, diverse and welcoming community that values and supports you.

You'll notice the importance we place on faculty-doctoral student interaction. The MEMS Graduate Student Committee plans seminars and social events—creating a strong community among Duke MEMS doctoral students.

Through programs like PhD Plus, students learn essential skills for their professional careers. Professional interests most often are realized through research and technology development careers.

Katy Hayes

"The US Air Force Research Laboratory was interested in me because of opportunities I had at Duke that showed I can communicate technical topics to an audience with diverse backgrounds."

Katy Hayes, PhD | Materials Research Intern

Regional Advantages

Our engineering quad is next to the Duke University Hospital, one of the world's leading academic medical research centers. In Durham, you'll enjoy outstanding restaurants, a thriving arts scene, and the Eno River State Park.

The Duke campus is just miles from Research Triangle Park (RTP), home to more than 200 major tech companies and a global hub for research.

To the west, are the Blue Ridge mountain towns of Asheville and Boone. To the east, the famous Outer Banks on the Atlantic coast. The cost of living in Durham is affordable—especially when compared to Boston, New York, Atlanta, and the San Francisco Bay Area.

Your Duke degree can take you anywhere in the United States and beyond. Some students choose to remain in our Research Triangle region, which is consistently ranked among the best places to live in the United States.

More about Durham, Duke's hometown »


More details

Degree Requirements

Degree Duke MEMS provides a customized, flexible educational experience tailored to meet your needs in your chosen research area. In our program, you will progress from introductory classes to specialized coursework. As you learn, your focus will gradually shift from coursework to learning important research and leadership skills.

  • 6-8 core courses, depending on your chosen curriculum 
  • Coursework-based Preliminary Exam in your 2nd year
  • Research-based Research Proposal Defense in your 3rd year
  • Complete Responsible Conduct of Research (RCR) training
  • Complete two semesters of teaching assistantship (TA)
  • Complete and defend a dissertation
  • During their training, many students also complete certificates
Certificates, Fellowships & Training Programs

Students can also pursue focused opportunities in areas of specialization and exploration, including:

  • Aerospace
  • AI for Understanding and Designing Materials
  • Biomolecular and Tissue Engineering
  • Medical Robotics
  • Nanoscience
  • Photonics
  • Public Policy
  • Surgical Technologies

More about Certificates, Fellowships & Training Programs »

Entering with Master of Science (MS) Completed

Students entering the PhD program with a master's degree from another institution should consult the Duke MEMS director of graduate studies and their advisor for possible substitution of other courses and/or waivers of some of these course requirements.

Teaching Assistantships

PhD students complete two semesters of Teaching Assistantship (TA). We provide training to help you develop your teaching skills.

It is expected that you will complete this requirement during your second through fourth years in the PhD program. TA assignments will be based on your background and interests, and department needs. The goal of your TA assignment is to provide you with a meaningful teaching experience based on your career goals.

Teaching Assistantships require 10 hours per week on average and may involve organizing and leading discussion sections, grading homework and quizzes, assisting in the development of course materials and supervising laboratory sessions.