Post-Doctoral Research Fellow - Molecular Epidemiology

Fred Hutch

(Seattle, Washington)
Full Time
Job Posting Details
About Fred Hutch

At Fred Hutch, our interdisciplinary teams of world-renowned scientists and humanitarians work together to prevent, diagnose and treat cancer, HIV/AIDS and other diseases. Our researchers, including three Nobel laureates, bring a relentless pursuit of, and passion for, health knowledge and hope to their work and the world.

Summary

The incumbent will work with a multidisciplinary team of investigators within a prostate cancer research program. A major focus of the current research is on inherited genetic susceptibility and molecular biomarkers involved in the development and progression of prostate cancer. This role is not a bench research-based position.

Responsibilities
  • Assume responsibility for analyses of epidemiological, genetic, epigenetic and gene expression data from population-based case-control studies, a population-based cohort of prostate cancer patients, and a study of high-risk hereditary prostate cancer families
  • Assist in the analyses of genetic/genomic/epigenomic variation in relation to prostate cancer risk and patient outcomes, including analyses of genome-wide association and linkage data, next-generation sequencing data, and genome-wide DNA methylation and gene expression data
  • Help with development of new grants and initiation of new research projects
  • Perform literature reviews
  • Generate and summarize research findings for scientific presentations
  • Prepare manuscripts for publication
Ideal Candidate
  • PhD in Epidemiology or related discipline
  • Knowledge of SAS/STATA and R/Bioconductor
  • Interest in prostate cancer genetics/genomics/epigenomics/molecular biology
  • Experience in cancer epidemiology and molecular epidemiology
  • At least one first-author, peer-reviewed publication
  • Strong organizational and analytical skills
  • Excellent writing and oral communication skills

Questions

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Seattle, Washington
Skills Desired
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  • Researching
  • SAS
  • STATA
  • R
  • Genomics
  • Epidemiology
  • Molecular Biology
  • Epigenomics

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