Principal Scientist, Computational Biology

Responsibilities

• Perform computational research and integrative analyses on multimodal biological profiling datasets (transcriptomic, proteomics, single-cell omics, spatial profiling) to support early pipeline programs.
• Apply machine learning and advanced computational/statistical approaches to compare high-dimensional perturbation readouts (CRISPR screens, perturb-seq, cellular imaging) to patient-defined disease states; nominate and validate new targets for Neuro, Cardiovascular, and Autoimmune indications.
• Collaborate with external partners (industry, academia, pre-competitive collaborations such as NIH AMP) on novel computational and experimental approaches.
• Communicate findings and recommend follow-up actions (1:1s, seminars, team meetings).

• PhD in a quantitative field (computational biology, computational genomics/genetics, computer science, statistics, mathematics, or related) and 5+ years post-graduate experience.
• Advanced hands-on knowledge of R or Python for computational and reproducible research.

• 5+ years post-graduate computational biology research experience (biopharma preferred) with publications/track record.
• Experience integrating high-dimensional multi-omics, single-cell (CITE-seq, scATAC-seq, perturb-seq), and/or spatial profiling.
• Strong statistical and ML skills (e.g., single-cell foundation models).
• Human disease biology background, especially autoimmune diseases.
• Experience with computer vision for cellular imaging; AI agent tools (e.g., Claude coding); strong self-learning and oral/written communication.

Cambridge, MA (no fully remote option)

$166,770–$202,086