Senior Scientist, AI Computational Structural Biology
$141,770–$179,601 year
On-site · San Diego, California, United States or Allston, Massachusetts, United States
Job Summary
Senior Scientist, AI Computational Structural Biology at BMS within the IPS Predictive Structure and Function team. Responsibilities include developing AI/ML models to predict structural biomolecular interactions for novel modalities, designing approaches to predict protein cooperativity and affinity from structures, building co-folding models using public and proprietary data, leveraging chemoproteomics data to generate novel druggability hypotheses, authoring scientific reports, and coordinating collaborative projects with academic and industry partners to advance AI-driven drug discovery. The role emphasizes applying AI/ML to structural biology, implementing state-of-the-art co-folding and structure-prediction workflows, and translating findings into actionable drug-discovery insights; requires advanced degrees and substantial experience in computational biology, AI/ML, and structural biochemistry; location-based compensation varies by site (Cambridge Crossing, MA and San Diego, CA).
Required Qualifications
- Bachelor's Degree with 7+ years academic/industry experience OR Master's Degree with 5+ years OR PhD with 2+ years;
- Proven AI/ML experience in biological contexts;
- Deep learning architectures for structural data (GNNs, equivariant networks, transformers, diffusion, flow matching);
- Hands-on experience with structure prediction/co-folding frameworks (AlphaFold2/Multimer, RoseTTAFold2, Boltz, Chai-1, NeuraPlexer, or equivalent);
- Proficiency in Python and libraries (PyTorch, JAX, RDKit, ESM/fair-esm, Biopython);
- Experience with chemoproteomics data, induced proximity modalities (e.g., PROTACs);
- Ability to publish methods/results to a high standard;
- Experience collaborating with academic/industry partners;
- Strong problem-solving and project-management skills;
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