Graduate Programs

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Scientific Computation Graduate Program

  The graduate degree program in scientific computation encompasses coursework and research on the fundamental principles necessary to use intensive computation to support research in the physical, biological, and social sciences and engineering. There is a special emphasis on research issues, state-of-the-art methods, and the application of these methods to outstanding problems in science, engineering, and other fields that use numerical analysis, symbolic and logic analysis, high-performance computing tools, parallel algorithms, supercomputing and heterogeneous networks, and visualization.

  Scientific Computation is gradually emerging as an important field of its own in academia and industry. In the last decade, it has become clear that solving a given scientific problem often requires knowledge that straddles several disciplines. This interdisciplinary program provides a new combination of studies for solving today's scientific computational problems. It is a degree program that builds on the strength of existing programs at the University of Minnesota in formulating real problems based on the physical system or the traditional discipline, and it augments field-specific work relating to the mathematical and numerical modeling with state-of-the-art techniques for scientific computation in an integrated manner.

  The Scientific Computation Program offers Ph.D. and M.S. degrees.

Computational Neuroscience Graduate Program

  This program introduces students with diverse biological and quantitative backgrounds to the challenges of complex phenomena in the neurosciences and fosters interdisciplinary training and research efforts toward meeting these challenges. Graduate Programs in Scientific Computation and Neuroscience are united with the Supercomputing Institute to provide a new paradigm for training graduate students interested in the physical, chemical, and computational sciences. This lowers the barriers to interdisciplinary research, provides opportunities for neuroscientists to pose problems to the quantitative sciences, and provides a catalyst for the cross-fertilization of the two disciplines. The Computational Neuroscience Program is funded in part by a National Science Foundation Integrative Graduate Education and Research Training (IGERT) grant.

This information is available in alternative formats upon request by individuals with disabilities. Please send email to alt-format@msi.umn.edu or call 612-624-0528.