Dana-Farber Cancer Institute – Computational Biologist Vacancy
Dr. Franziska Michor’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. Michor’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:
- 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
