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.
A post-doctoral research fellowship is now open at the Fred Hutchinson Cancer Research Center. The fellow will be primarily involved in development and application of statistical methodology within the context of high-dimensional genomic and microbiome studies, but the specific areas of methodological research can be flexible, depending on the fellow's interests and skills.
The fellow will be supervised by Dr. Michael Wu and will have the opportunity to interact with other statistical faculty in the program as well as the opportunity to collaborate with top scientists at Fred Hutch and across the country.
The fellow will be involved in development and application of methods for high-dimensional genomic data, such as genetic, metabolomic, and microbiome data. Many challenges exist for analyzing these new types of data, providing exciting opportunities for the development of novel statistical methods. With the data being directly collected from forefront research projects, this work has the potential to be truly high-impact. The fellow will also have the opportunity to interact with leading experts in biomedical science, and to establish a broad research network for their future career.
+ Ph.D. or equivalent in Statistics, Biostatistics or in a similar quantitative field
+ Excellent written and oral communication skills
+ Strong computing skills (R)
+ Experience with statistical methods for high dimensional data and with genomic data analysis are a plus
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