Fred Hutchinson Cancer Research Center, home of three Nobel laureates, is an independent, nonprofit research institution dedicated to the development and advancement of biomedical research to eliminate cancer and other potentially fatal diseases. Recognized internationally for its pioneering work in bone-marrow transplantation, the Center's five scientific divisions collaborate to form a unique environment for conducting basic and applied science. The Hutchinson Center, in collaboration with its clinical and research partners, the University of Washington and Seattle Children's, is the only National Cancer Institute-designated comprehensive cancer center in the Pacific Northwest. Join us and make a difference!
Project teams and Faculty within the Biostatistics and Biomathematical Program employ statistics and mathematical principles to analyze biological and genetic data and processes and evaluate diagnostic, therapeutic and preventive medical methods and practices. Project teams and faculty also provide statistical collaboration and coordination for research programs within and outside the center, develop and evaluate new quantitative methods for the efficient design and analysis of a broad range of biomedical studies and construct biomathematical models of carcinogenesis and other biological processes.
The Biostatistics and Biomathematics Program at the Fred Hutchinson Cancer Research Center's Division of Public Health Sciences is recruiting a post-doctoral research fellow to work with a senior faculty member (Biostatistician). Fellow will engage in both methodological and collaborative research with areas focused on disease risk prediction and novel prognostic biomarker evaluations. Fellow will have opportunities to participate in large collaborative projects and large-scale genome-wide association studies.
Applicants should have Ph.D. in statistics or biostatistics or other quantitative area. Strong theoretical, computational, and communication skills (verbal and written) are desired. In particular, a successful candidate should be able to write efficient programs in R (in addition, working knowledge of SAS is a plus), and have basic theoretical training in survival analysis. Background in longitudinal data analysis is a plus. The position is available immediately and for up to three years.
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