Scientific Computation Applications Courses
Applications Courses are intended to expose students to computational methods and mathematical modeling as may be relevant to their science discipline.
I. Requirements
These courses will be selected from a list of courses offered by the various Departments and approved by the Graduate Committee for the Program. The content of approved courses must be primarily in mathematics or computational science. Each student's Study Advisory Committee, working with the student, will recommend a set of Applications courses.
Like the core science courses, Applications Courses should be selected with advice from the Departments that teach the courses. Students planning their programs should make sure the courses they choose are being taught regularly. The following examples illustrate courses that might be appropriate for the Scientific Computation program.
Optimization
- ENCH 737 Chemical Process Optimization
- ENME 610, 625 Engineering Optimization I and II
- AMSC 764 Advanced Numerical Optimization
- BMGT 831 Operations Research: Linear Programming and Network Analysis
Applied Numerical Methods PDE/ODE
- AMSC 763 Advanced Linear Numerical Analysis
- AMSC 715 Numerical Methods for Evolution Partial Differential Equations
- AMSC 714 Numerical Methods For Stationary PDEs
- ENME 674 Finite Element Methods
- ENAE 653 Nonlinear Finite Element Analysis
Numerical Methods in Sciences
- ASTR 698C Computational Astrophysics
- ENAE 652 Computational Structural Mechanics
- ENAE 684,685 Computational Fluid Dynamics I and II
- ENCH 739 Modern Computing Techniques in Process Engineering
- ENEE 789C: Advanced topics in electrophysics: numerical methods in electromagnetism
- ENME 645, 646 Computational Fluid Dynamics and Heat Transfer I and II
- AOSC 614-625 Numerical Weather Forecasting & Data Assimilation
- STAT 798C Computational Methods in Statistics
- AOSC 614 Atmospheric Modeling, Data Assimilation and Predictability
- STAT 705 Computational Statistics
- CMSC 828D
- CMSC 828V Advanced topics: Numerical Methods for Data Science and Machine Learning
Mathematical/Statistical Modeling in Sciences
- ENCE 630,730 Environmental and Water Resource Systems I and II
- ENCE 731 Advanced Ground Water Hydrology
- ENCH 753 Aerosols and Particulate Science
- ENCH 869 Advanced Computer-Aided Process Engineering
- ENEE 644: Computer-aided design of digital systems
- ENEE 694: Physics and simulation of semiconductor devices
- ENME 616 Computer-Aided Manufacturing
- ENSE 621 Systems Engineering Principles
- ENSE 622 System Modeling and Analysis
- GEOL 789C: Computational GeoScience: Data Handling and Analysis
- ZOOL 625 Mathematical Biology