Graduate Programs

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. The current Director of Graduate Studies is Jiali Gao of the Department of Chemistry.

Computational Neuroscience Training Program

The Computational Neuroscience Program is a unique interdisciplinary study and research program that combines neuroscience and computation. The program requires the use of quantitative methods and computer- related analysis techniques to study the development, structure, and function of the nervous system. The Supercomputing Institute is united with graduate programs in Biochemistry, Molecular Biology and Biophysics, Biomedical Engineering, Chemical Engineering, Chemistry, Chemical Physics, Computer Science, Mathematics, Neuroscience, Physics, and Scientific Computation to provide a new paradigm for training graduate students interested in neuroscience and computation. 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 Traineeship (IGERT) grant. The Executive Committee consists of Timothy J. Ebner, Neuroscience, and Donald G. Truhlar, Supercomputing Institute Director, Chemistry, Chemical Physics, and Scientific Computation.