Post-Doctoral Research Fellow, Statistical Genetics

Post-Doctoral Research Fellow, Statistical Genetics

Fred Hutchinson Cancer Research Center

Seattle, WA, United States

Post-Doctoral Research Fellow, Statistical Genetics


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 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.


James Dai’s research group seeks a post-doctoral fellow in statistical genetics and genomics.

The fellow will work closely with James Dai and other group members to develop statistical methodologies and computational algorithms in the areas of genetic epidemiology, cancer genetics, epigenetics and genomics. They will lead manuscript writing in statistics and genetics, and present methods and discoveries in meetings and conferences. The fellow will also engage with collaborators in epidemiology, genomics and medicine, providing statistical consultation and technical support.


The successful candidate will have a demonstrated ability to identify and address statistical challenges from epidemiologic and biological questions, develop rigorous statistical and computational methods, and implement methods through efficient programs and algorithms. The candidate will have effective communication and writing skills to present in statistical and genetic meetings, provide consultations and lead manuscript writing.

Qualified candidates must have at least a PhD degree in Bioinformatics, Genomics, Biostatistics, or related quantitative field. In addition, preferred candidates will have experience in collaborating with research scientists and performing bioinformatics/genomics data analysis.

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Quote Reference: 12041