Cures Start Here. At Fred Hutchinson Cancer Research Center, home to three Nobel laureates, interdisciplinary teams of world-renowned scientists seek new and innovative ways to prevent, diagnose and treat cancer, HIV/AIDS and other life-threatening diseases. Fred Hutch’s pioneering work in bone marrow transplantation led to the development of immunotherapy, which harnesses the power of the immune system to treat cancer. An independent, nonprofit research institute based in Seattle, Fred Hutch houses the nation’s first and largest cancer prevention research program, as well as the clinical coordinating center of the Women’s Health Initiative and the international headquarters of the HIV Vaccine Trials Network. Careers Start Here.
Technology advances have made it possible to characterize tumor features (e.g., somatic mutations) in large numbers of tumors, providing a unique opportunity to understand tumor heterogeneity and how it is associated with clinical outcomes and the underlying germline genetic and environmental etiology. Dr. Li Hsu's group in the Biostatistics Program is recruiting one post-doctoral research fellow. The specific areas of interest include statistical genetics and genomics, multiple hypothesis testing, statistical and machine learning. The fellow will engage in methodological research for analyzing tumor genomics and germline genetics data. They will have real-hand data analysis experience by participating in large collaborative studies, in which rich data on tumor somatic mutation, germline genetics and environmental risk factors have been collected on a very large number of study participants.
The position will come with a competitive postdoc-level salary with great benefits for two years, with the possibility of extension. The environment at Fred Hutch is lively yet casual, with a strong emphasis on innovative and collaborative work. The Center is housed in a lovely campus next to Lake Union a short walk from downtown, and a convenient shuttle from the University of Washington.
Applicants should have a Ph.D. in statistics, biostatistics or computational biology with emphasis in statistical genomics/genetics, hypothesis testing and machine learning. Strong biological and computational skills are desired. In particular, a successful candidate should be able to write efficient programs in R and/or C. The position is available immediately and for up to two years