Immuno-Oncology – Computational Biologist / Senior Computational Biologist

About the position

The scientist in this computational role will form a key part of a team driving forward the drug development process, from target and hit identification to pre-clinical and IND-enabling studies, to enable development of new immuno-oncology based medicines for cancer patients. The scientist in this role will work closely with other computationalists and domain experts to inform and move the process forward. This role is based in our Cambridge, MA location.



  • Writing code to run standard bioinformatics tools and Immuneering internal platforms (R preferred)
  • Interpreting outputs in biological context in immuno-oncology, helping to build biological story
  • Identifying, QCing, analyzing and interpreting genomic, primarily transcriptomic, datasets
  • Designing, analyzing and interpreting experimental results with guidance from domain experts
  • Reviewing code from internal project collaborators
  • Interfacing with platforms group to iterate on helpful platform features


Core qualifications

  • PhD in computational biology or related field (e.g., biology, bioinformatics, engineering, computer science) or 5+ years of work experience at a leading biology / computational biology focused institution
  • Ability to code cleanly in R (preferred) or Python
  • Experience with version control (e.g. git) and code review
  • Biology background in immuno-oncology or related field
  • Demonstrated ability to apply computational approaches to transcriptomic and/or other high-throughput molecular data
  • Demonstrated experience interpreting results of computational analyses in a biological context
  • Familiarity with publicly available molecular databases and experience QCing, analyzing and interpreting publicly available molecular datasets
  • Strong communication and presentation skills
  • Proven ability to work independently as well as to contribute to larger initiatives


 Preferred additional qualifications

  • Expertise in single-cell RNA sequencing analyses
  • Experience working to support the drug development process
  • Research relevant to patient stratification
  • Experience using Docker / similar for environment control
  • Experience applying machine learning approaches to answer biological questions


To apply, contact ATTN: Immuno-Oncology Hiring Manager