Computational Biologist – Principal Scientist - #104
Repertoire Immune Medicines
 Cambridge, MA

We are founded on the premise that the repertoire of T cell receptor-antigen interactions that drive health and disease represents one of the greatest opportunities for innovation in medical science. Repertoire also sees data and computational methods as strategic assets on par with biologics and is building a first-in-kind platform bringing all of these elements together to decode the immune synapse and deploy the resulting insights to the treatment, cure and prevention of cancer, autoimmune conditions and infectious diseases.

Reporting to the Head of Computational Sciences, the successful candidate will pursue novel interdisciplinary work that engages the entire company. As a senior member of the computational team, s/he will lead the development and application of a range of bioinformatics analysis methods and exploratory software tools for interrogating multimodal data from the platform, engage continuously with the Molecular Biology, Technology Development, Protein Sciences and Therapeutics groups in iterative development of the platform, guide the interpretation of internal and external datasets to inform selection of therapeutic targets (e.g. tumor-associated antigens) as well as mentor junior team members.

Required Experience and Skills:

  • Typical incumbent has a Ph.D. in Computational biology, Biostatistics, Bioinformatics, Computer Science, or Genetics. Exceptional M.S. candidates may also meet criteria
  • 12+ years of relevant experience including biotech/pharma settings
  • Multi-omic bioinformatics, statistics, data modeling and analysis
  • Analysis and interpretation of large-scale DNA and RNA sequence data (bulk and single cell, e.g. CellRanger)
  • High-throughput computation using cloud infrastructure (preferably AWS)
  • Programming proficiency in at least 2 of Python, R, SQL; some UNIX exposure
  • Strong communication skills (oral and written) and attention to detail
  • Capable of working from incomplete information, with little supervision
  • Able to systematically prioritize deliverables across multiple projects
  • Open, collaborative mindset of a mission-driven, team player
  • Strong drive and resilience in the face of challenges, with positive attitude
  • Evidence of ability to translate external research publications into actionable outcomes aligned with organizational goals

Preferred Experience and Skills:

  • Background in immunology and cancer immunotherapy is a strong plus
  • Development of exploratory visual tools with Jupyter/PANDAS or Shiny
  • Experience analyzing flow cytometry data
  • Machine learning experience
  • Familiarity with multi-omic data cleansing and integration
  • Strong publication record