Senior Computational Chemist - Oncology Targeted Discovery
Core
Design and select next-generation targeted medicines using structure-based design, ligand-based approaches, and AI/ML to guide oncology discovery programs.
Role type
Senior IC computational chemist (oncology drug discovery)
Builds
Predictive models, design hypotheses, and prioritized compound lists for hit-to-lead success
Domain
Oncology + Computational Chemistry + AI/ML
Deliverable
production ML models
Required skills
Structure-based drug design, ligand-based drug design, quantum mechanics, molecular dynamics, AI/ML software toolkits (RDKit, ChemProp, DeepChem, PyTorch, scikit-learn), hypothesis-driven design
Preferred skills
Experience with antibody–drug conjugates, bifunctional agents, proximity-inducing agents
Technologies
RDKit, ChemProp, DeepChem, PyTorch, scikit-learn
Responsibilities
Generate testable design hypotheses integrating structural insights and biophysical data; Apply docking and pharmacophore modeling to prioritize compounds; Build and deploy predictive models for high-throughput experiment design; Develop computational methods for new modalities; Partner with medicinal chemistry, biology, and DMPK teams; Present results to stakeholders and contribute to publications
Seniority
Senior, hands-on IC
