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Dana-Farber Cancer Institute – Computational Biologist Vacancy

Dana-Farber Cancer Institute – Computational Biologist Vacancy

Dr. Franziska Michorโ€™s lab at the Dana-Farber Cancer Institute and Harvard University is looking for a motivated Associate Computational Biologist to work full time on the Cancer Immunologic Data Commons (CIDC) project. CIDC is the data coordination and distribution center for the NCI-sponsored Cancer Moonshot initiative called the ImmunoOncology Biomarkers Network (https://cimac-network.org/). CIDC collects and processes data from four centers nationwide: Dana-Farber Cancer Institute, Icahn School of Medicine at Mount Sinai, MD Anderson Cancer Center, and Stanford University. Dr. Michorโ€™s group is responsible for supporting the bioinformatics analysis for the clinical trials from the network. The successful candidate will address methodological and computational challenges related to the integrative analyses of a variety of data types including CyTOF, whole-exome sequencing, RNA-sequencing, TCR-sequencing, ATAC-sequencing, and imaging-based data types.

Job Title: Associate Computational Biologist, Michor Lab

Eligibility Criteria:

  • BSc or MSc graduates in Biological Sciences with an interest in Biomedical Data Science.
  • Students taking gap years (>= 2 years) to accumulate computational biology research experience towards future Ph.D. or MD applications.
  • People with programming skills along with an interest in cancer genomics and a willingness to learn.

Requirements

  • Maintain and develop NGS sequencing pipelines in the Google Cloud Platform.
  • Run pipelines to process incoming sequencing data generated from clinical trials.
    Collaborate with laboratory researchers to perform downstream analysis and generate biological insights from clinical trial data.
  • Communicate results to immediate collaborators, as well as bioinformatics and clinical communities.
  • Perform cross-trial analysis integrating multiple data types in the CIDC data portal to identify new biomarkers for immunotherapy using statistical modeling or machine learning approaches.
  • Implement and document reliable and efficient web applications with well-designed user interfaces.

Preferred:ย 

  • Undergraduate or master’s degree in a quantitative field.
  • Experience developing software or analyzing data using Python or R.
  • Experience in web development or computational pipeline development in both cluster and cloud environments is preferred.
  • Prior genomics or bioinformatics research experience is a plus but not required.

Opportunities

  • Opportunity to learn bioinformatics in a friendly environment.
  • Opportunity to be involved in cross-trial analysis and to have an impact on cancer immunotherapy.
  • Opportunity to contribute to software projects that will help a broad community of cancer researchers finds better ways to treat cancer.
  • Opportunity to work in an interdisciplinary environment with cancer epigenetics, immunology, computational biology, and machine learning experts.
  • Opportunity to work closely with the software engineer team in the Knowledge Systems Group (KSG) at DFCI.

Dana-Farber Cancer Institute

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