Computational Associate II - Cancer Data Science

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 an informal, collegial environment. You'll help to develop pipelines for and find exciting results in new types of CRISPR experiments. Your work in both the Golub Lab and the Cancer Dependency Map project will build research experience across a wide spectrum of computational biology. 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.

What the job involves

• Design and execute data analysis strategies to support research projects involving multimodal cancer datasets, such as RNA-seq (single-cell and bulk), WES, CRISPR, RNAi, drug sensitivity screens and more.
• Together with other team members develop new methods for predictive modeling of high-dimensionality genomic data.
• Explore new machine learning approaches for integrating diverse clinical and preclinical data.
• Conceive, implement and test statistical models.
• Work with wet-lab researchers to analyze data from experiments.
• Write manuscripts describing research results.
• Develop analytical and software tools for distribution to the global cancer research community.

Requirements:

• Bachelor's degree + Masters in a STEM field (or Bachelors with 2+ years of experience working in analytical STEM)
• Ability to engage with and solve unfamiliar problems.
• Scientific curiosity.
• Team player, strong communicator: people will depend on your work, and you will depend on theirs.
• Fluent, reliable coder (python or R preferred)
• Presence on-site for some portion of the work week.
• At least some knowledge of data science topics such as probability, statistics and machine learning; experience applying this knowledge preferred.