Principal Scientist, Computational Biology
Bristol Myers Squibb
6 days ago
On-site
Cambridge, MA
Other
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; help nominate and validate new Neuro, Cardiovascular, and autoimmune targets.
- Collaborate with external partners (industry, academia, pre-competitive collaborations) on novel computational and experimental approaches.
- Communicate findings and recommend follow-up actions (1:1s, seminars, team meetings).
Basic Qualifications:
- Bachelor’s degree (computational biology/genomics/genetics, CS, statistics, math, or related) + 8+ years academic/industry experience.
- Or Master’s degree + 6+ years academic/industry experience.
- Or PhD + 4+ years academic/industry experience.
Preferred Qualifications/Skills:
- Hands-on R or Python; 5+ years post-graduate computational biology research (biopharma preferred).
- Experience with multi-omics, single-cell (CITE-seq, scATAC-seq, perturb-seq), and spatial profiling (Xenium, Visium, GeoMx, CosMX).
- Statistical methodology and ML experience; human disease biology (neurodegenerative, cardiovascular, autoimmune) strongly preferred.
- Computer vision on cellular imaging preferred; experience with AI agents (e.g., Claude coding) preferred.
- Strong oral/written communication.
Compensation Overview (Cambridge): $166,770 - $202,086.
- 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; help nominate and validate new Neuro, Cardiovascular, and autoimmune targets.
- Collaborate with external partners (industry, academia, pre-competitive collaborations) on novel computational and experimental approaches.
- Communicate findings and recommend follow-up actions (1:1s, seminars, team meetings).
Basic Qualifications:
- Bachelor’s degree (computational biology/genomics/genetics, CS, statistics, math, or related) + 8+ years academic/industry experience.
- Or Master’s degree + 6+ years academic/industry experience.
- Or PhD + 4+ years academic/industry experience.
Preferred Qualifications/Skills:
- Hands-on R or Python; 5+ years post-graduate computational biology research (biopharma preferred).
- Experience with multi-omics, single-cell (CITE-seq, scATAC-seq, perturb-seq), and spatial profiling (Xenium, Visium, GeoMx, CosMX).
- Statistical methodology and ML experience; human disease biology (neurodegenerative, cardiovascular, autoimmune) strongly preferred.
- Computer vision on cellular imaging preferred; experience with AI agents (e.g., Claude coding) preferred.
- Strong oral/written communication.
Compensation Overview (Cambridge): $166,770 - $202,086.