RTG: Research Training in Mathematical and Computational Biology

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This RTG program will continue the development of a comprehensive program of cross-disciplinary research and training in Mathematical and Computational Biology, housed within the Department of Mathematics at the University of Utah. The training component will give students a high level of mathematical training, substantial exposure to biological problems and techniques, and extensive experience in communication and collaboration with experimental life scientists. The research component will develop and use mathematical and computational methods to study complex biological processes, organized around four major research themes of biofluids, ecology and evolutionary biology, neuroscience and physiology. The training of students in this program will include traditional and non-traditional coursework, journal clubs, seminars, laboratory rotations, extramural research experiences, research group meetings, mentoring, consulting and teaching experiences, as well as a variety of professional development experiences. Students will receive research mentoring by mathematicians and experimentalists in a highly interactive setting in which they learn the necessary biology and develop the ability to do non-traditional, cross-disciplinary, cutting edge research. This program will train fully integrated, collaborative researchers, scholars and educators in mathematical and computational biology, thus bringing to bear the power of mathematics on the challenging problems of modern biology. Many collaborative research projects will be initiated as a result of our research training paradigm, as students become engaged with other students and faculty in other departments and institutions. By placing quantitatively trained individuals in an environment where medical and biological problems are at the forefront, the possibilities for new insights and discoveries are truly outstanding. The long term effect of this program will be a new generation of applied mathematical scientists who can work effectively to build bridges between traditional disciplines and among academia, industry and the public sector.