Students completing this program will:

• Be prepared to join and contribute to interdisciplinary teams in scientific research or industry.
• Have a firm understanding of the physical theory and computational strategies used in the student's major discipline. This includes the ability to select the most appropriate algorithm for the problem.
• Understand the computational methods used in the industry standard software packages in the student's major discipline.
• Have a general knowledge of the computational methods used in other areas and their potential application to the student's major discipline.
• Have a solid foundation in numerical methods and a general understanding of statistical data analysis.
• Understand computer architectures used in modern scientific computation.
• Be familiar with currently used programming languages for scientific computing (C, FORTRAN 90 and FORTRAN 77) including optimization techniques.
• Have an in-depth understanding of parallel algorithm development and other methods and tools required for high performance computing.
• Be able to apply the tools of visualization to the analysis of scientific data and produce images/animations that extract the essential information and display it so the relevant content is clear.
• Have demonstarated ability in creating useful tools for computational scientific research. The tools needed are those that are powerful and flexible enough to solve a variety of real problems, safe to run and optimized enough to handle large problems.