Principal Scientist, Computational Biology
Bristol Myers Squibb
June 30, 2026
Remote friendly (Cambridge, MA)
United States
Clinical Research and Development
Responsibilities:
- Perform computational research and integrative analyses on multimodal biological profiling datasets (e.g., transcriptomic, proteomics, single-cell omics, spatial profiling) designed with wet lab scientists to support early pipeline programs.
- Apply machine learning and advanced computational/statistical approaches to compare high-dimensional perturbation readouts (e.g., CRISPR screens, perturb-seq, cellular imaging) to patient-defined disease states; help nominate and validate new targets for Neuro, Cardiovascular, and Autoimmune indications.
- Collaborate with external partners (industry, academia, and pre-competitive collaborations such as NIH Accelerating Medicines Partnership) on novel computational and experimental approaches.
- Communicate findings and recommend follow-up actions in 1:1s, seminars, and team meetings.
Basic Qualifications:
- 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 at least one high-level programming language (R or Python) for computational and reproducible research.
Preferred Qualifications:
- 5+ years post-graduate computational biology research experience (biopharma preferred), with a track record (e.g., publications).
- Experience integrating high-dimensional multi-omics, single-cell, and/or spatial profiling; implementing statistical/ML methods (e.g., single-cell foundation models).
- Background in human disease biology (autoimmune strongly preferred); computer vision for cellular imaging preferred.
- Experience with AI agents (e.g., Claude coding) and strong oral/written communication.
Compensation (Cambridge Crossing): $166,770 - $202,086.
Application instruction:
- Apply even if your experience doesn’t perfectly match.
- Perform computational research and integrative analyses on multimodal biological profiling datasets (e.g., transcriptomic, proteomics, single-cell omics, spatial profiling) designed with wet lab scientists to support early pipeline programs.
- Apply machine learning and advanced computational/statistical approaches to compare high-dimensional perturbation readouts (e.g., CRISPR screens, perturb-seq, cellular imaging) to patient-defined disease states; help nominate and validate new targets for Neuro, Cardiovascular, and Autoimmune indications.
- Collaborate with external partners (industry, academia, and pre-competitive collaborations such as NIH Accelerating Medicines Partnership) on novel computational and experimental approaches.
- Communicate findings and recommend follow-up actions in 1:1s, seminars, and team meetings.
Basic Qualifications:
- 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 at least one high-level programming language (R or Python) for computational and reproducible research.
Preferred Qualifications:
- 5+ years post-graduate computational biology research experience (biopharma preferred), with a track record (e.g., publications).
- Experience integrating high-dimensional multi-omics, single-cell, and/or spatial profiling; implementing statistical/ML methods (e.g., single-cell foundation models).
- Background in human disease biology (autoimmune strongly preferred); computer vision for cellular imaging preferred.
- Experience with AI agents (e.g., Claude coding) and strong oral/written communication.
Compensation (Cambridge Crossing): $166,770 - $202,086.
Application instruction:
- Apply even if your experience doesn’t perfectly match.