BACKGROUND

RESPONSIBILITIES

• Computational and statistical analysis of cancer genome and transcriptome sequencing studies,
• Expansion of existing computational capabilities to more effectively identify additional types of mutations and splice variants,
• Assessment of immune-related gene expression in tumor, stroma and T- and B-cell populations,
• T-cell TCR repertoire analysis and
• Computational analysis of patient samples in support of ongoing clinical trials.

• Methods development- analysis of RNA-seq data for splicing and gene fusion events; population and individual rearranged TCR and BCR repertoire; integrating multiple clinical and immunological data sets to identify novel discoveries and directions
• Ongoing support of a clinical effort in neoantigen discovery and application
• Self-directed computational research

REQUIREMENTS

• Ph.D. in mathematical, physical, computer science or engineering.
• At least two years post-PhD as post-doc or within a company is desired. Preferably with a focus on computational solutions to biological or engineering problems.
• Ability to apply statistical and machine learning techniques to solve "big data" problems.
• Strongly preferred experience in one of the following programming languages: C#, C++, Java, Lua, Objective-C, Python, Ruby or Scala (Java, Scala or Python especially favored).
• Exceptional candidates without experience in those programming languages but with excellent MATLAB or R skills and experience will also be considered.
• Strong desire to focus on computational biological applications.
• Ability to work in a highly collaborative and intellectually challenging environment.
• Excellent oral and written communication skills, to conduct both self-directed and guided computational research.

LOCALE

HOW TO APPLY