Post-Doctoral Research Fellow, Computational and Statistical Cancer Genomics
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.
SWOG is one of five national recognized cooperative oncology groups in the National Clinical Trials Network. The SWOG Statistics and Data Management Center (SDMC) located in Seattle Washington at Fred Hutch, provides leadership in the statistical design, data management, analysis, and reporting of NCTN clinical trials. It contributes to SWOG’s overall mission to significantly improve lives through cancer clinical trials and translational research.
The fellow will be involved in developing and/or applying cutting edge strategies for analyzing genomic data within the context of cancer clinical trials and translational studies. Both methodologists and applied quantitative researchers are encouraged to apply. The data are from important cancer trials providing exciting opportunities for generating significant clinical and translational findings. At the same time, many challenges exist for analyzing these data, providing exciting opportunities for development of novel statistical and computational approaches. The fellow will also have the opportunity to interact with leading experts in a range of disciplines and biomedical science, and to establish a broad research network for future career development.
- PhD in Biostatistics, Bioinformatics, Computational Biology, Computer Science, Statistics or other relevant discipline.
- Familiarity with genomic data and approaches for high-dimensional data analysis.
- Strong written and oral communication skills.
Successful applicants will submit their CV, cover letter, and contact information for three references.
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