Senior Scientist, AI Computational Structural Biology

Senior Scientist, AI Structural Biology

When you join BMS, you become part of a diverse, high‑achieving team working to pioneer, partner, and predict transformative insights for patient benefit. The Informatics and Predictive Sciences (IPS) mission conducts applied computational research in genomics, structural and molecular informatics, systems biology, patient selection, translational biomarker research, and machine learning across all therapeutic areas. This role will shape AI‑driven drug discovery within our induced proximity and targeted protein degradation programs, collaborating with scientists in Protein Homeostasis, Computational Sciences, Oncology, and other IPS teams.

• Develop AI/ML models to predict structural biomolecular interactions for novel modalities leveraging protein–protein interactions.
• Design innovative AI/ML approaches to predict protein cooperativity, affinity, and other biological properties based on structures.
• Develop co‑folding models that incorporate structural and non‑structural priors using public and proprietary BMS data.
• Develop AI/ML models that leverage chemoproteomics data to generate novel druggability hypotheses for hard-to‑drug targets.
• Author scientific reports and present methods, results, and conclusions to publishable standard.
• Contribute to the planning and execution of collaborative projects with leading academic and commercial research groups worldwide.

• Bachelor’s Degree with 7+ years of academic/industry experience
• Or Master’s Degree with 5+ years of academic/industry experience
• Or PhD with 2+ years of academic/industry experience

• Ph.D. in Computational Biology, Bioinformatics, Structural Biology, Computer Science, Chemistry, or a closely related field with >2 years post‑doctoral experience in AI/ML approaches in drug discovery.

• Proven experience developing and deploying AI/ML models in biological or biochemical contexts, proficient in deep learning architectures for structural data (GNNs, equivariant neural networks, transformers, diffusion, flow matching) using Python and libraries such as PyTorch, JAX, RDKit, ESM/fair‑esm, Biopython.
• Deep expertise in protein–protein interactions, protein folding, and biomolecular complex formation; hands‑on experience with structure prediction and co‑folding frameworks (Alpha
  
  Fold2, Alpha Fold‑Multimer, RoseTTAFold2, Boltz, Chai‑1, Neura Plexer, or equivalent).

• Ability to integrate and analyze multimodal datasets—including structural, genomic, and proteomic data—from public and proprietary sources, and develop algorithms to interpret genomics and proteomics data.
• Familiarity with chemoproteomics data for druggability and ligandability assessment; experience with induced proximity modalities (e.g., PROTACs, molecular glues, bifunctional molecules) is appreciated but not required.

• Strong problem‑solving mindset with ability to design novel computational approaches for challenging biological questions.
• Experience contributing to or leading collaborative research projects with academic and/or industry partners, translating scientific findings into actionable drug discovery insights.
• Self‑motivated with strong organizational skills and ability to manage multiple projects simultaneously.
• Demonstrated ability to present complex methods and results to diverse scientific audiences and to author high‑quality scientific reports and publications to publishable standard.

Cambridge Crossing: $148,210 – $179,601
San Diego, CA, US: $141,770 – $171,794

• Health Coverage:
  Medical, pharmacy, dental, and vision care.
• Well‑being Support:
  Programs such as BMS Well‑Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP).
• Financial Well‑being and Protection: 401(k) plan, short‑ and long‑term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support.

• US Exempt Employees: flexible time off (unlimited, with manager…