Graduate Training in Computational and Systems Biology

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DESCRIPTION (provided by applicant): The objective is to continue development of MIT's interdisciplinary predoctoral graduate training program in Computational and Systems Biology (CSB) which trains students to become leaders in biomedical research at the interface of biology, computation and engineering. The CSB Ph.D. program is a core component of MIT's Computational and Systems Biology Initiative (CSBi;.http://csbi.mit.edu), an institute-wide initiative that spans a variety of collaborative and interdisciplinary research, educational and community efforts in the field. Program faculty are concentrated in the three founding departments - Biological Engineering (BE), Biology, and Electrical Engineering & Computer Science (EECS) - with additional involvement of faculty from other departments. Faculty from these departments have research programs spanning a broad set of topics in computational and systems biology, including gene and protein network modeling and reconstruction, cell and tissue engineering, bioimaging and image informatics, regulatory genomics, proteomics, predictive toxicology and metabolic engineering, nanobiology and microsystems, computational biophysics, and integrative cancer biology. This proposal seeks to expand the pool of training faculty by more than a dozen, including 7 faculty newly hired in the past 4 years who have active research programs in the field. Students apply directly to the CSB Ph.D program from their undergraduate or Master's institution and receive multi- and inter-disciplinary training in the field of computational and systems biology. The proposal seeks to support 8 students for the first two years of the Ph.D., enabling extended research rotations and participation in unique program activities. Unique aspects of the program include: (a) close association with the multi- and inter-disciplinary research agenda of SBi and of the participating labs; (b) a unique core formed from newly developed, inter-disciplinary classroom subjects that combine biology, engineering, statistics and computation; (c) intensive advising and multi-disciplinary thesis committees to optimize the training experience for students from diverse academic backgrounds; (d) a seminar series program with active student participation focusing on leading edge research both within and outside of MIT; (e) an annual symposium and an annual retreat with participation of students and faculty focusing on research, leadership, and challenges to interdisciplinary research.