PhD Program
Take on the Biggest Challenges Facing Humanity and the Planet
Earning a PhD takes courage. There will be obstacles, uncertainty and ambiguity. But it’s the vision of a better world that drives you. That’s what drives us, too.
Comprehensive Mentorship & Support
Comprehensive mentoring is the cornerstone of our PhD experience. Once admitted, we help you assemble an advising team to include your research advisor, departmental advisor, the director of graduate studies, a five-member dissertation committee and the department chair.
Additional Amenities
- Support for conference attendance and travel
- Access to externally-funded traineeship programs
- Graduate certificates in tissue engineering, nanoscience and photonics
Research Study Tracks
As a department that integrates mechanical engineering and materials science, we can offer multiple, rigorous yet flexible pathways to a PhD.
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Six courses, with at least one each in Structures & Dynamics; Aerodynamics, Acoustics & Fluid Mechanics, and Mathematical & Computational Methods
Structures & Dynamics
- ME 541: Intermediate Dynamics
- ME 544: Advanced Mechanical Vibrations
- ME 527: Buckling
Aerodynamics, Acoustics & 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 & Computational Methods
Important Note
No more than two in this category may 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
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Six courses total from across Materials, Computation and AI & Materials Integrated.
Materials
Select three:
- 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 510: Diffraction and Spectroscopy
- ME 511: Computational Materials Science
- ME 512: Modern Materials
- ME 514: Theoretical and Applied Polymer Science
- ME 515: Electronic Materials
- ME 519: Molecular Modeling of Soft Materials
- ME 555 Intermediate Polymer Physics
- ME 562: Materials Synthesis and Processing
- ME 563: Fundamentals of Soft Matter
- ME 564: Introduction to Polymer Physics
- ME 711: Nanotechnology Materials Lab
- PHYS 516: Quantum Materials
Computation
Select one from Course Set A and one from Course Set B:
Course Set A
- CS 570: Artificial Intelligence<
- CS 671D Theory and Algorithms for Machine Learning
- ECE 580: Introduction to Machine Learning
- ECE 590: Deep Learning
- ECE 682D: Probabilistic Machine Learning
- MEMS 555/CEE 690: Data Science and machine learning for Engineers
Course Set B
- CEE-690: Uncertainty Quantification in Computational Science and Engineering
- ME 511: Computational Materials Science
- ME 519: Molecular Modeling of Soft Materials
- ME 524: Introduction to the Finite Element Method
- ME 525: Nonlinear Finite Element Analysis
- ME 555: Numerical Optimization
AI & Materials Integrated
Select one:
- ME 555: Data and Materials Science Applications
- ME 555: Sci Computing, Simulation and ML
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Six courses, with at least one each in Math & Computational Methods, Mechanics & Fluids, and Biology & Medicine
Math & 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 & Fluids
- BME 528: Biofluid Mechanics
- CE 541: Structural Dynamics
- ME 555: Intro to Rheology
- ME 572: Engineering Acoustics
Biology & 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
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Six courses, with at least one each in Applied Math, Numerical Methods, Engineering Sciences & Mechanics, and Computer Sciences/Programming
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 & 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
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Six courses, with at least one each in Math & Statistics, Dynamics & Controls, and Computational Methods
Math & Statistics
- ME 555: Numerical Optimization
- MATH 561: Numerical Linear Algebra
- MATH 577: Mathematical Modeling
- ECE 586: Vector Space Methods
- BA 911: Convex Optimization
Dynamics & 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
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Six courses from across Solid-State Materials, Statistical Thermodynamics, Quantum Mechanics, Course Set A and Course Set B:
Solid-State Materials
Choose one:
- CHEM 548: Solid-State/Materials Chemistry
- ECE 524: Introduction to Solid-State Physics
- PHYS 516: Quantum Materials
- ME 555: Modern Materials
Statistical Thermodynamics
Choose one:
- CHEM 544 Statistical Mechanics
- PHYS 563 Introduction to Statistical Mechanics
- PHYS 763 Statistical Mechanics
Quantum Mechanics
Choose one:
- ECE 521: Quantum Mechanics, or
- Other graduate-level quantum mechanics course
Course Set A
Select two:
- 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
Course Set B
Select one:
- 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
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Six courses from across Hard Matter, Statistical Thermodynamics, Polymers and Course Set A
Hard Matter
Select one:
- CHEM 548: Solid-State/Materials Chemistry
- ECE 524: Introduction to Solid-State Physics
- PHYS 516 Quantum Materials
- ME 555: Modern Materials
Statistical Thermodynamics
Select one:
- CHEM 544 Statistical Mechanics
- PHYS 563 Introduction to Statistical Mechanics
- PHYS 763 Statistical Mechanics
- ME 555: Fundamentals of Soft Matter
Polymers
Select two:
- 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
Course Set A
Select one:
- 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
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Six courses, with at least one each in Energy, Fluids and Applied Math & Numerical Methods
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 & Numerical Methods
- MATH 551: Applied Partial Differential Equations
- ME 524: Finite Element Method
- ME 639 Computational Fluid Dynamics and Heat Transfer
Doctor of Philosophy in Mechanical Engineering & Materials Science
Duke provides a customizable educational experience that you design to meet your needs and the area of research you choose.
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In our program, PhD students progress from introductory courses to specialized coursework.
As you learn, your focus gradually shifts from coursework to learning critical research and leadership skills.
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- 6 to 8 core courses, depending on the curriculum you choose
- Preliminary Exam, based on coursework, in your second year
- Research Proposal Defense in your third year
- Complete Responsible Conduct of Research (RCR) training
- Complete two semesters of teaching assistantship (TA)
- Complete and defend a dissertation
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Students entering this 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.
PhD Contacts
Stefan Zauscher, Associate Chair, Director of Graduate Studies and Professor in the Thomas Lord Department of MEMS
Michell Tampe, Graduate Studies Program Coordinator