Principal Scientist, Computational Chemistry
Core
Applying in silico technologies and AI/ML to drive the discovery of lead-like molecules against hard-to-drug therapeutic targets.
Role type
Principal Scientist, Computational Chemistry
Builds
Virtual screening workflows, predictive models for library design, and triage data for hit-to-lead optimization.
Domain
Biopharmaceutical drug discovery
Deliverable
production ML models | product features
Required skills
virtual screening, HTS triaging, hit calling, diversity analysis, protein modeling, AI/ML integration, SAR analysis, physiochemical property analysis, ADMET analysis, homology-based chemistry mining, ensemble docking, molecular dynamics, free energy calculations
Preferred skills
expertise in ligand- and structure-based methods, experience with DEL (DNA-encoded libraries), experience with large dataset analysis
Technologies
Python, R, Schrödinger, OpenEye, RDKit, GROMACS, AMBER, PyTorch, TensorFlow
Responsibilities
Deliver virtual screening workflows leveraging physics- and AI-based modeling methods; Provide computational chemistry program support across the drug discovery pipeline; Provide guidance on modern cheminformatics and ML/AI methods for library design and predictive modeling; Routinely employ expert knowledge for SAR, physiochemical, and ADMET property analysis; Work alongside medicinal chemists to triage emerging hits for synthesis/purchase; Collaborate with data science teams to integrate AI/ML tools into chemistry processes.
Seniority
Principal, hands-on IC with strategic oversight