PhD and MS Study Tracks

Core Requirements

Core requirements consist of six (6) courses in total:

  • 1 mathematics course, and
  • 1 computational methods course

and, either:

Mathematics Courses

  • MATH 551(211): Applied Partial Differential Equations and Complex Variables (F)
  • MATH 577(229): Mathematical Modeling (S)
  • Or, a more advanced course with approval of the Director of Graduate Studies and instructor

Computational Methods Courses

  • ME 639(229): Computational Fluid Mechanics and Heat Transfer (F)
  • ME 524(254)/CE 530(254): Finite Element Method (F)
  • MATH 561(224): Scientific Computing
  • COMPSCI 520(250): Numerical Analysis
  • Or, a more advanced course with approval of the Director of Graduate Studies and instructor

Study Track - Mechanical Engineering

Students pursuing a mechanical engineering study track must take a total of four (4) courses from the five MEMS Mechanical Engineering core concentrations, doubling up in one core and taking one course from two other core areas.

The material presented in these core courses constitutes the knowledge that should be tested in the qualification examination following the first year of graduate studies.

Note for PhD students: Courses other than those currently listed in the cores can be approved by the Director of Graduate Studies in consultation with the advisor. This may be necessary to fulfill requirements for certificate or training grant programs.

Each recommended course is in italics and marked with an asterisk (*).

CORE 1: Mechanics, Dynamics and Controls

Solid Mechanics

  • *CE 520(201): Continuum Mechanics (F) 
  • *CE 521(206): Theory of Elasticity (S)
  • CE 621(203): Plasticity 
  • BME 530(230): Tissue Biomechanics
  • ME 525(255)/CE 630(255): Nonlinear Finite Element Analysis
  • ME 527/CEE 647, Buckling of Engineering Structures
  • CE 645(281): Experimental Systems

Dynamics

  • *ME 541(210)/CE 625(210): Intermediate Dynamics (F)
  • ME 543(234): Energy and Wave Propagation in Solids
  • ME 544(235): Advanced Mechanical Vibrations
  • ME 544(236): Engineering Acoustics
  • CE 541(283): Structural Dynamics
  • ME 742(335): Non-Linear Mechanical Vibrations
  • ME 555(265): Advanced Acoustics
  • ME 555(265): Acoustic Cavitation
  • ME 555(265): Therapeutic Ultrasound
  • ME 555(265): Energy Harvesting from Vibration

Controls

  • *ME 545(270): Robot Control and Automation (F)
  • *ME 546(233): Intelligent Systems (S)
  • ECE 555(255): Methods for Systems Analysis

Aerodynamics

  • *ME 571(237): Aerodynamics (F)
  • *ME 775(325): Aeroelasticity
  • ME 671(238): Advanced Aerodynamics
  • ME 672(239): Unsteady Aerodynamics
  • ME 555(265): Rockets and Gas Turbines

CORE 2: Thermal Fluids

Thermodynamics

  • *ME 531(202): Engineering Thermodynamics
  • *ME 532(280): Convective Heat Transfer (F)

Fluid Mechanics and Transport Phenomena

  • *ME 631(226): Intermediate Fluid Mechanics (F)
  • ME 536(221): Compressible Fluid Flow (F)
  • ME 632(227): Advanced Fluid Mechanics
  • ME 759(399): Hydrodynamic Stability
  • ME 307(207)/BME 307(207): Transport Phenomena in Biological Systems
  • ME 555(265): Microscale Physicochemical Hydrodynamics

CORE 3: Materials Science

General Materials Science

  • *ME 512(218): Thermodynamics of Materials (S)
  • ME 215: Advanced Materials Science
  • PHYS 563(203): Introduction to Statistical Mechanics
  • ME 711(303): Advanced Materials Laboratory

CORE 4: Robotics

The Robotics Core allows PhD and MS students to focus on the interdisciplinary techniques needed to be a successful robotics engineer. Below are suggested courses and sample degree plans for students interested in this concentration area.

Learn more about our Robotics Concentration for master's students.

Key Courses

  • ME 555/ECE 590: Introduction to Robotics and Automation
  • ME 627: Linear Systems Theory
  • ME 555: Systems Engineering
  • ME 555/ECE 590: Human-Robot Interaction
  • ME 555/ECE 590: Advanced Robot System Design
  • COMPSCI 527: Computer Vision
  • COMPSCI 570: Artificial Intelligence
  • COMPSCI 571D: Machine Learning
  • COMPSCI 590: Advanced Topics in CS: Algorithmic Aspects of Machine Learning
  • ME 545: Robot Control and Automation
  • ME 546: Intelligent Systems
  • ME 555: Intelligent Sensors
  • ME 524: Introduction to the Finite Element Method
  • ME 542: Modern Control and Dynamic Systems
  • STA 611: Intro to Mathematical Statistics
  • STA 561: Probabilistic Machine Learning
  • CEE 625(210)/ME 541: Intermediate Dynamics
  • CEE/ME 648: Multivariable Control
  • CEE 690: System Identification
  • ECE 551: Programming, Data Structures, and Algorithms in C++
  • ECE 555: Probability for Electrical and Computer Engineers
  • ECE 581: Random Signals and Noise
  • ECE 590: Vector Space Methods With Applications
  • ECE 681: Pattern Classification and Recognition Technology
  • STA 611: Intro to Mathematical Statistics
  • STA 561: Probabilistic Machine Learning
  • STA 643: Modern Design of Experiments
  • STA 641 Statistical Learning and Bayesian Nonparametrics
  • STA 621 Applied Stochastic Processes

Master's Sample Degree Plans

Robotics is a broad discipline, and there are a variety of sub-specializations for master's students to choose from. Here we give two example degree plans for robot design and control and intelligent systems sub-specializations. There is some flexibility in each of these plans, and a fourth course each semester should be taken according to your interests and to fulfill degree requirements.

Sub-Specialization: Robot design and control

First Year — Fall semester

  • ME 555/ECE 590: Introduction to Robotics and Automation
  • ME 627: Linear Systems Theory
  • ECE 551: Programming, Data Structures, and Algorithms in C++

First Year — Spring semester

  • ME 542: Modern Control and Dynamic Systems
  • ME 524: Introduction to the Finite Element Method
  • CEE 690: System Identification

Second Year — Fall semester

  • CEE 625(210)/ME 541: Intermediate Dynamics
  • STA 611: Intro to Mathematical Statistics
  • ME 555: Systems Engineering

Second Year — Spring semester

  • ME 555/ECE 590: Advanced Robot System Design
  • CEE/ME 648: Multivariable Control
  • Additional electives, independent study, or MS final project

Sub-Specialization: Intelligent systems

First Year — Fall semester

  • ME 555/ECE 590: Introduction to Robotics and Automation
  • ME 627: Linear Systems Theory
  • ECE 551: Programming, Data Structures, and Algorithms in C++

First Year — Spring semester

  • ME 555/ECE 590: Human-Robot Interaction
  • ECE 555: Probability for Electrical and Computer Engineers or STA 611: Intro to Mathematical Statistics
  • A machine learning, artificial intelligence, or computer vision course

Second Year — Fall semester

  • ME 555: Systems Engineering
  • MATH 561: Scientific Computing
  • A machine learning, artificial intelligence, or computer vision courses

Second Year, Spring semester

  • ME 555/ECE 590: Advanced Robot System Design
  • STA 611: Intro to Mathematical Statistics
  • Additional electives, independent study, or MS final project

CORE 5: Aerospace

Structures and Dynamics

  • ME 427: Aerospace Structures
  • ME 544(235): Advanced Mechanical Vibrations
  • ME 555: Systems Engineering
  • ME 572(236): Engineering Acoustics
  • CE 541(283): Structural Dynamics
  • ME 742(335): Non-Linear Mechanical Vibrations
  • ME 555(265): Advanced Acoustics

Aerodynamics

  • ME 472: Aircraft Performance
  • ME 571(237): Aerodynamics (F)
  • ME 775(325): Aeroelasticity
  • ME 671(238): Advanced Aerodynamics
  • ME 672(239): Unsteady Aerodynamics
  • ME 555(265): Rockets and Gas Turbines

Math and Computational Methods (2 Courses)

  • MATH 551(211): Applied Partial Differential Equations and Complex Variables (F)
  • MATH 577(229): Mathematical Modeling (S)
  • ME 639(229): Computational Fluid Mechanics and Heat Transfer (F)
  • ME 524(254)/CE 530(254): Finite Element Method (F)
  • MATH 561(224): Scientific Computing
  • COMPSCI 520(250): Numerical Analysis

Study Track - Materials Science

Students pursuing the materials science study track must take a total of four (4) courses from the MEMS Materials Science core concentrations, covering at least three of the four cores.

The material presented in these core courses constitutes the knowledge that should be tested in the qualification examination following the first year of graduate studies.

Note for PhD students: Courses other than those currently listed in the cores can be approved by the Director of Graduate Studies in consultation with the advisor. This may be necessary to fulfill requirements for certificate or training grant programs.

Each recommended course is in italics and marked with an asterisk (*).

CORE 1: General Materials Science

  • *ME XXX: Advanced Materials Science
  • *ME 512(218): Thermodynamics of Materials (S)
  • PHYS 563(203): Introduction to Statistical Mechanics
  • ME 711(303): Advanced Materials Laboratory

CORE 2: Solid Materials and Photonics

  • *ME 555(265): Introduction to Solid State Engineering
  • ME 515(212): Introduction to Electronic Materials 
  • PHYS 810(310): Advanced Solid State Physics
  • ME 759(399): Electrons and Phonons in Solid State Engineering
  • ECE 511(310): Foundations in Nanoscience and Technology
  • ME 555(265): Optical Properties of Nanomaterials
  • ECE 545(225): Nanophotonics
  • ECE 590(299): Advanced Optics
  • ECE 590(299): Advances in Photonics

CORE 3: Soft Materials/Interfaces

  • *ME 512(211)/BME 529(208): Theoretical and Applied Polymer Science
  • BME 525(215)/ME 519(215): Biomedical Materials
  • BME 570L(220): Introduction to Biomolecular Engineering 
  • ME 555(265): Fundamentals of Electrochemistry
  • ME 555(265): Electromagnetism of Fluids
  • ME 555(265): Fundamentals of Physical Surface Chemistry
  • ECE 590(299): Biochip Engineering

CORE 4: Characterization

  • *ME 711(303): Advanced Instrumentation
  • BME 550(234): Modern Microscopy
  • ME 555(265): Scanning Probe Microscopy
  • ECE 590(299): Imaging and Spectroscopy