Predictive Science and Engineering Design Certificate

The following requirements are in addition to, or further elaborate upon, those requirements outlined in The Graduate School Policy Guide.


Total Units Required: 5

Course Requirements:

To earn a graduate certificate in Predictive Science and Engineering Design, a student must enroll in at least 5 approved courses (three core courses plus two electives).

Course Title
Core Area 1: PSED Seminar
This is a literature and project combined seminar course focusing on the common principles and techniques underlying Predictive Science and Engineering Design (PS&ED). In addition to learning the fundamental principles and techniques associated with PS&ED, students will work in teams on interdisciplinary projects related to the current design focus of PS&ED.
Predictive Science & Engineering Design Cluster Seminar
Predictive Science & Engineering Design Cluster Seminar
Core Area 2: Modeling, Simulation, and High Performance Computing
This topic introduces the next generation of advanced computational methods for predictive simulation of multiscale, multiphysics phenomena. Topics include molecular dynamics, lattice mechanics, methods of thermodyanmics, statistical mechanics, multiscale modeling, bridging scale methods, supercomputing, etc. Students will also become proficient in computing technology, including numerical computation and the practical use of advanced computer architectures.
Applied Molecular Modeling
Advanced Finite Element Methods 1
Advanced Finite Element Methods I
Advanced Finite Element Methods 2
Advanced Finite Element Methods II
Introduction to Parallel Computing
Stochastic Simulation
Special Topics (Atomic-Scale Computational Materials Science)
Multi-scale Modeling and Simulation in Solid Mechanics
Multi-Scale Modeling and Simulation in Fluid Mechanics
Core Area 3: Computational Design Methods
This topic provides students across all disciplines a view of using computational techniques (including topics like modeling, simulation, optimization, uncertainty quantification, risk-based decision making) and the simulation-based design paradigm for designing complex “engineered” systems based on predictive models.
Simulation Experiment Design & Analysis
Materials Design
Computational Methods for Engineering Design
Special Topics in Mechanical Engineering (Mechanistic Data Science for Engineering)
Engineering Optimization for Product Design and Manufacturing
Electives (2 required courses)
Biomechanics of Movement
Applied Mathematical Statistics
Reliability Engineering
Experiments in Micro- and Nano Science and Engineering
The Calculus of Variations and Its Applications (Optimization Methods in Science and Engineering)
Metal Forming
Advanced Tribology