Description & Requirements
The Cancer Data Science team’s mission (http://www.cancerdatascience.org/) is to accelerate cancer research with data-driven innovation and machine learning. Situated in the Broad’s Cancer Program, we design experiments, interpret the results, and present them to the public. Along the way, we develop new statistical tools and machine learning methods, write papers, produce datasets that are used by tens of thousands of researchers around the world, and help guide research and development for applying new technologies to cancer research.
In this role, you will work closely with experimental and computational scientists in a scientific and collegial environment. You will lead the computation efforts on projects focused on the evaluation and interpretation of ‘omics data in cancer cell line models. You’ll be the first to see large new datasets produced with cutting edge experimental techniques at one of the premier biological research facilities in the world. Our computational scientists have opportunities to collaborate with renowned research scientists and build valuable research experience. By applying your computational and modeling skills to multimodal cancer data you will find new biological insights and help advance our understanding of cancer.
The Broad Institute provides a vibrant research environment with close links to top academic institutions and research hospitals across the Boston area, providing unique opportunities for your contributions to have direct clinical impacts and to be used and recognized worldwide.
In this role, you will:
Perform large scale computational analysis of datasets derived from various Omics modalities, including but not limited to single-cell and bulk RNA sequencing, WGS, long read sequencing (genomic and transcriptome), ATAC-seq
Benchmark new computational methods for Omics analysis
Learn and apply machine learning and statistical modeling where applicable
Conduct exploratory data analysis and visualization to understand results of analysis pipelines
Stay up-to-date on computational methods and cancer biology by means of deep literature reviews
Present analysis results to team for feedback and iterative development
REQUIREMENTS
PhD(with 0+ years experience) or MS(with 4+ years experience) in quantitative field (preferably Computational Biology or Bioinformatics)
Excellent coding skills in Python; demonstrated experience in clean coding practices and thorough documentation (a github link would be helpful)
Demonstrated experience with NGS and genomic analysis
Ability to engage with and solve unfamiliar problems
Thinking critically and holistically about analytical results from multiple data sources and how to create biological impact
Team player, strong communicator: people will depend on your work, and you will depend on theirs
Presence on-site for some portion of the work week