Senior Scientist, AI Computational Structural Biology

Working with UsChallenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us.Senior Scientist, AI Structural BiologyWhen you join BMS, you are joining a diverse, high-achieving team united by a common mission. The Informatics and Predictive Sciences (IPS) mission is to Pioneer, Partner and Predict to drive transformative insights for patient benefit.  IPS conducts applied computational research in areas that include genomic, structural and molecular informatics, computational and systems biology, patient selection and translational biomarker research, and broader fields including knowledge science, epidemiology and machine learning—across the full lifecycle of drug discovery and development and across all therapeutic areas at BMS.   We do this in close partnership with scientific and clinical experts in the field, both inside and outside the company.   We perform innovative science to empower key data-driven decisions across a rich pipeline of next-generation medicines. In doing so, our work transforms the lives of patients, as well as our own lives and careers.Here, you’ll get the chance to grow and thrive through opportunities that are uncommon in scale and scope. You’ll pursue innovative ideas while advancing professionally alongside some of the brightest minds in biopharma.This is a unique opportunity to shape the next generation of AI-driven drug discovery at BMS, with direct impact on our induced proximity and targeted protein degradation programs. We are seeking a collaborative and highly innovative computational biologist with a strong background in AI co-folding modeling and deep understanding of protein structures to join our Predictive Structure and Function team.They will work alongside scientists in Protein Homeostasis, Computational Sciences, Oncology and other teams in the Informatics and Predictive Sciences (IPS) department to discover novel target opportunities leveraging protein-protein interactions and apply learnings to other small and large molecule modalities.Responsibilities: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 & other biological properties based on structures.Develop co-folding models that incorporate structural and non-structural priors using combinations of public and proprietary BMS data.Develop AI/ML models that leverage chemoproteomics data contributing to the generation of 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.Basic Qualifications:Bachelor's Degree 7+ years of academic / industry experience Or Master's Degree 5+ years of academic / industry experienceOr PhD 2+ years of academic / industry experiencePreferred Qualifications:Ph.D. in Computational Biology, Bioinformatics, Structural Biology, Computer Science, Chemistry, or a closely related field, with a strong focus on AI/ML applications in drug discovery with 2+ years of post-doctoral experience in developing AI/ML approaches in university, pharma, or biotech settings, focusing on drug discovery.Requirements - Technical Skills & Experience:AI/ML & Deep Learning: Proven experience developing and deploying AI/ML models in biological or biochemical contexts, with proficiency in deep learning architectures for structural data (GNNs, equivariant neural networks, transformers, diffusion, flow matching) using Python and relevant libraries (PyTorch, JAX, RDKit, ESM/fair-esm, Biopython, etc.).Structural Biology and Co-folding: Deep expertise in protein-protein interactions, protein folding, and biomolecular complex formation, with hands-on experience in structure prediction and co-folding frameworks (e.g. AlphaFold2, AlphaFold-Multimer, RoseTTAFold2, Boltz, Chai-1, NeuraPlexer, or equivalent).Preferred Skills:Multi-Omics Data Integration:Multi-Omics Data Integration:Multi-Omics Data Integration: Ability to integrate and analyze multimodal datasets—including structural, genomic, and proteomic data—from both public and proprietary sources, with experience developing algorithms to interpret genomics and proteomics data.Chemoproteomics & induced proximity: Familiarity with chemoproteomics data for druggability and ligandability assessment is preferred. Experience with induced proximity modalities (for example, PROTACs, molecular glues, and bifunctional molecules) is appreciated but not required.Requirements - Scientific & Collaborative Skills:Strong problem-solving mindset with the ability to design novel computational approaches for challenging biological questions.Experience contributing to or leading collaborative research projects with academic and/or industry partners and ability to translate scientific findings into actionable drug discovery insights.Self-motivated with strong organizational skills and the ability to manage multiple projects simultaneously.Demonstrated ability to presenting