Post-doc Position Available – Computational Cancer Genomics

Overview

The laboratory of Dr. Alice Berger is recruiting highly motivated post-doctoral research fellows to perform computational biology research in the field of cancer genetics and genomics.

About the Lab

The Berger lab focuses on application and development of functional genomics approaches for understanding somatic mutations in cancer, with a focus on lung cancer. The lab utilizes genomics approaches for oncogene discovery (Imielinski, Berger et al., Cell 2012; TCGA, Nature 2014) and functional genomics approaches for understanding the mutation function (Berger, Brooks, Wu et al., Cancer Cell 2016). The mission of the lab is to open up new therapeutic opportunities for lung cancer.

The lab is generating massive genomics datasets using RNA-seq, single-cell RNA-seq, ChIP-seq and exome sequencing both in experimental cell line systems and also human primary samples.

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.

Responsibilities

We are looking for talented computational biologists to develop computational methods and lead genome analysis projects. The successful applicant will be highly collaborative and will interact closely with wet lab biologists from project inception to completion. The candidate will be expected to be have strong programming skills in R, C/C++ and/or Python. The candidate will implement novel computational and statistical approaches for analyzing and visualizing next-gen sequencing data with a goal of understanding the function of somatic mutations in cancer.

Qualifications

We are looking for exceptional candidates with a recent PhD, and/or MD and a track record of independent productive research. A strong research record in computational and statistical approaches for genomics analysis is required. Experience with RNA-seq analysis or analysis of public–omics data (e.g. TCGA) is highly desirable. Exceptional candidates will have experience with cancer genome analysis and knowledge of cancer biology and signal transduction. Excellent written and verbal communication skills in English are required.

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