Computational Mechanics & Scientific Computing Master of Engineering

Model and test systems virtually

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scientific formulae on a computer screen

Prepare for a Career Developing Model-Based Simulations

Duke’s Master of Engineering in Computational Mechanics and Scientific Computing is one of the most comprehensive in the world—and features a top-notch faculty.

More and more systems are designed and tested virtually.

Success requires solid knowledge of engineering physics, computer science, probability, data sciences and applied mathematics—this master’s degree provides strong foundations in each of those over a three-semester study plan.

Duke will help get you there. Rare for professional master’s programs, we offer scholarships—up to $30,000 to competitive applicants.

The problem-solving skills I learned were the most valuable part of my Duke experience.
Huidi Ji Development Engineer

Duke Chapel and Abele Quad at Duke University — Fall color appears along Chapel Drive, Duke University

Previous Engineering Training Not Required

An engineering degree is suitable, but not required.

If you have an interest in computer modeling and have a background in physics, computer science or mathematics—this may be an ideal master’s degree program for you.

Prepare for a career in:

Additive manufacturing
Design of industrial products and biomedical devices
Design and analysis of infrastructure
Noise and vibration analysis
Vehicle crashworthiness simulation

Scholarships

Typically $20,000 to $30,000 for competitive applicants.

Contact admissions

Curriculum

30 credits:

Core Industry Preparation Courses (6 credits)
Departmental, Disciplinary or Cross-Disciplinary Requirements (12 credits)
Technical Electives in Application Areas (12 credits)

- MENG 540: Management of High Tech Industries (3 credits)
- MENG 570: Business Fundamentals for Engineers (3 credits)
- MENG 550: Internship or Applied Research Project (0 credits)
- MENG 551: Internship/Project Assessment
- CE 530 / ME 524: Introduction to the Finite Element Method
- CE 630 / ME 525: Nonlinear Finite Element Method
Choose one:
- Math 561: Numerical Linear Algebra
- Math 541: Applied Stochastic Processes
- Math 551 Applied Differential Equations and Complex Variables
Choose one:
- CS 590: Parallel Computing
- ECE 551D: Programming, Data Structures, and Algorithms in C++
Choose four courses total; at least one in each application area:

Mechanics of Materials
- CEE 520: Continuum Mechanics
- CEE 541: Structural Dynamics
- ME 555: Computational Materials Science
- CEE 622: Fracture Mechanics
Fluid Mechanics
- CEE 531: Finite Element Methods for Problems in Fluid Mechanics
- ME 572: Engineering Acoustics
- ME 639: Computational Fluid Mechanics and Heat Transfer
- CEE 690: Turbulence
Optimization / Data Analytics
- CS-445/MATH-465: Intro to High Dimensional Data Analysis
- CE 522 / ME 526: Numerical Optimization
- CS-571D: Machine Learning
- STA 502: Bayesian Inference and Decision
Important Note

Other course offerings may be substituted with consent of the Director of Masters Studies.
CE 703/ME 703: Industrial Colloquia in Computational Mechanics & Scientific Computing

Typical Study Plan

Category	Fall 1	Spring 1	Summer 1	Fall 2
Core Industry Preparation Courses	MENG 570 Business Fundamentals for Engineers	MENG 540 Leadership & Management Principles for Technology-Based Organizations	MENG 550 Internship or Applied Research Project	MENG 551 Internship/Project Assessment
Finite Element Method Courses	CEE 530/ME 524 Introduction to the Finite Element Method	CEE 630/ME 525 Nonlinear Finite Element Method
Applied Math/Statistics Course	MATH 561 Numerical Linear Algebra
Computer Science Course		CS 590 Parallel Computing
Technical Electives	Elective 1	Elective 2		Elective 3 Elective 4
Proseminar	CE 703/ME 703 Industrial Colloquium in Computational Mechanics & Scientific Computing