Computational Biologist – Principal Scientist - #104

Research & Development Cambridge, Massachusetts


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