Computational Associate II - Cancer Program

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 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 associates have opportunities to be mentored by 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.

Our Computational Associates:

• 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 (PRISM), 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 help design experiments and analyze the resulting data.
• Write manuscripts describing research results.
• Develop analytical and software tools for distribution to the global cancer research community.

We pride ourselves on the quality of our science, but just as much on our work culture. We believe in a team with a healthy work-life balance and a high degree of psychological safety. We look for candidates with diverse backgrounds, strengths, and perspectives, who are willing to challenge and be challenged.