Senior Scientist, AI Computational Structural Biology
Core
Develop AI/ML models to predict structural biomolecular interactions, protein cooperativity, and affinity for novel drug modalities including PROTACs and molecular glues.
Role type
Senior IC AI computational structural biologist
Builds
Production AI/ML models for protein-protein interaction prediction and druggability assessment
Domain
Biopharma / Structural Biology / Machine Learning
Deliverable
production ML models
Required skills
Deep learning architectures for structural data (GNNs, equivariant networks, transformers, diffusion, flow matching), Python, PyTorch, JAX, RDKit, ESM/fair-esm, Biopython, protein-protein interaction analysis, protein folding, co-folding frameworks (AlphaFold2, AlphaFold-Multimer, RoseTTAFold2, Boltz, Chai-1, NeuraPlexer)
Preferred skills
Multi-omics data integration (structural, genomic, proteomic), chemoproteomics data analysis, induced proximity modalities (PROTACs, molecular glues, bifunctional molecules)
Technologies
PyTorch, JAX, RDKit, ESM, fair-esm, Biopython, AlphaFold2, AlphaFold-Multimer, RoseTTAFold2, Boltz, Chai-1, NeuraPlexer
Responsibilities
Develop AI/ML models to predict structural biomolecular interactions; Design innovative AI/ML approaches to predict protein cooperativity and affinity; Develop co-folding models incorporating structural and non-structural priors; Develop AI/ML models leveraging chemoproteomics data for druggability hypotheses; Author scientific reports and present methods/results to publishable standard; Contribute to planning and execution of collaborative projects with academic and commercial research groups
Seniority
Senior, hands-on IC