Tri-Institutional PhD Program in Computational Biology & Medicine

Weill Medical Coll Of Cornell Univ, New York NY

Investigators

Linked publications & trials

Abstract

The Tri-Institutional PhD Program in Computational Biology and Medicine (CBM) takes advantage of the outstanding educational and research resources of the Tri-Institutional (Tri-I) consortium in New York City – Weill Cornell Medical College (WCM), Cornell University’s medical campus; Memorial Sloan Kettering Cancer Center (MSK), comprising the basic science Sloan Kettering Institute (SKI) and research programs in Memorial Hospital (MH); and The Rockefeller University (RU) – together with Cornell University, both through its main campus in Ithaca, NY (CU-I) and its newer Cornell-Tech (CTech) campus in New York City, to train the next generation of computational biologists. The CBM provides training in the computational and quantitative approaches needed to tackle complex multidisciplinary biomedical problems and provides: coursework in both quantitative and biological sciences; research rotations to enable a well-informed thesis topic selection; mentored thesis research in one of a wide array of basic to translational laboratories; trainee Research-in-Progress seminar series to enhance program cohesion, foster fluency in relevant disciplines, and provide opportunities for scientific presentation practice; training and mentorship in performing rigorous and reproducible scientific research; an array of programmatic enrichment activities, including an annual offsite retreat which provides cross-lab and cross-campus interactions, lunches with visiting seminar speakers, and fellowship writing training; active guidance and mentoring via annual formal meetings with program co-Directors, annual thesis committee meetings that include career discussions, and annual IDPs; exposure to various career paths for successful transition into the biomedical research workforce. The Program, which is well established with a 21-year track record, has an expanding record of training success, including timely graduation and a strong record of placing graduates in research-related careers both in and outside academia. With this proposal, we are requesting 10 T32 slots (compared to 8 slots in our previous T32), which is well justified by the deep pool of highly qualified training-grant eligible applicants, large array of cutting-edge thesis research opportunities with leading faculty scientists, and the training enrichment that is inherent to an increased critical mass of students. The requested T32 funding would greatly aid the CBM program in continuing to achieve its mission of excellence in training the next generation of scientists to rigorously and reproducibly develop and apply computational and analytical methods to solve complex problems in biology and medicine and to prepare them for research-related academic and non-academic careers following timely completion of their PhD degrees.