University of Texas at Austin

Overview

The Master of Science (MSc) in Interdisciplinary Program in Computational Science, Engineering and Mathematics (CSEM) at the University of Texas at Austin equips students with the skills to leverage advanced computational techniques for solving complex problems across various scientific and engineering domains. The program is designed to foster a deep understanding of computational principles while encouraging interdisciplinary collaboration.

Students have the opportunity to engage with esteemed faculty and research groups affiliated with the Oden Institute, gaining access to cutting-edge high-performance computing and visualization resources that enhance their learning experience.

What you'll study

The MSc CSEM program offers a blend of rigorous coursework and research training. Students will typically undertake core and elective courses tailored to their specific interests, culminating in a research project under faculty guidance.

Coursework areas may include:

• Tools and Techniques of Computational Science
• Computer Graphics
• Numerical Analysis: Linear Algebra
• Numerical Analysis: Interpolation, Approximation, Quadrature, and Differential Equations
• Statistical and Discrete Methods for Scientific Computing
• Theory of Probability
• Mathematical Statistics
• Methods of Applied Mathematics
• Real and Complex Analysis

Research component: Students are required to engage in graduate-level research as part of their degree. The specifics of this requirement, including the format (thesis or capstone project), will be outlined in the official degree plan.

Interdisciplinary options: Students may align their research and electives with various application areas available at UT Austin and the Oden Institute, including computational medicine, computational geosciences, and computational engineering.

Entry requirements

Career prospects

Graduates of the MSc in CSEM program are well-prepared for a variety of career paths in academia, industry, and research institutions. Potential roles include computational scientists, data analysts, software engineers, and research scientists. The interdisciplinary nature of the program allows graduates to adapt to the evolving demands of the workforce, making them valuable assets in fields such as technology, healthcare, environmental science, and engineering.