Undertaking innovative cancer research can require input from teams of scientists with a mixture of backgrounds, including molecular biology, oncology, medicine, genetics, epidemiology, biostatistics, and computer science. Researchers with interdisciplinary training across these fields are extremely valuable to such teams, as they can act as catalysts for the integrated work necessary to accomplish some of the most promising and cutting edge cancer research. Due to the focused nature of training within these fields, however, there are limited opportunities for investigators to obtain knowledge that bridges these disciplines. This program provides postdoctoral training in the computational genomic epidemiology of cancer. This program defines a novel, transdisciplinary area of training at the intersection of cancer research, genetics, epidemiology, biostatistics, and computer science. The programs' structure is defined by three key requirements. First, all fellows will take a specialized core curriculum of five courses that cover the individual discipline at all of the intersections. Second, the fellows will undertake additional didactic experiences selected to complement their educational and research background. Third, all fellows will obtain research experience by collaborating on focused projects with multiple mentors from different disciplines. As an extension of this research experience, each trainee will be required to write a mock NIH proposal. Cancer researchers obtaining training in this program will have the skills vital to deciphering the complex pathways comprised of genetic and environmental risk factors for disease, and will ultimately be able to provide clinicians and their patients with valuable information for the prevention and treatment of cancer.
This postdoctoral fellowship provides a salary of $63,000 per year, most benefits, and up to $20,000 per year for research supplies and travel to conferences.
Candidates must be U.S. citizens or permanent residents.
Click here for application instructions.