EMSW21-RTG: Research Training Group in Mathematical and Computational Biology

University Of Utah, Salt Lake City UT

Investigators

Abstract

0354259 Keener Research Training in Mathematical and Computational Biology Abstract: The investigator and his colleagues will continue development of a comprehensive program of cross-disciplinary research and training in Mathematical and Computational Biology. The goal of this program is to bring to bear the power of mathematics on the challenging problems of modern biology by initiating collaborative research projects with a wide variety of laboratory life scientists and by training young mathematicians and computational scientists in the art of cross-disciplinary research. The research program will develop and use mathematical and computational models to study complex biological processes, organized around four major research themes of biofluids, ecology and evolutionary biology, neuroscience and physiology. This program will begin to address the critical need for more people with high-level mathematical skills who have the ability to contribute in a significant way to the many challenging problems of biological and medical significance. The program will impact young mathematical scientists at the undergraduate, graduate, and postdoctoral levels, and will provide an environment in which collaboration across levels and across disciplines is the norm rather than the exception. Research projects will involve investigators from several fields with the result that all participants will receive mentoring from several individuals. Educational and training activities supporting this research will include coursework, journal clubs, laboratory group meetings (SIG's or Special Interest Groups), seminars and workshops, laboratory experience and internships. Together, these vehicles of training will help to develop young researchers with a broad knowledge of mathematical and computational biology coupled with expertise in specific biological problems. The long-term effect of this program will be to produce a new generation of applied mathematical scientists who will work effectively to build bridges between traditional disciplines and academia, industry and the public sector.