Executive Director, AIRx Computational Chemistry
Core
Drive in silico molecular design, leverage predictive models, and apply generative chemistry to power rapid drug discovery cycles, directly shaping candidates that advance to the clinic.
Role type
Executive Director, Computational Chemistry (Scientific Lead)
Builds
AI-powered operating models for drug discovery, virtual screening campaigns, and predictive ADMET models
Domain
Pharmaceutical drug discovery, computational chemistry, AI/ML in chemistry
Deliverable
production ML models
Required skills
Generative AI for molecular design, structure-based drug design, free energy perturbation (FEP), molecular docking, MD simulation, QSAR/ADMET modeling, Python programming, ML model deployment, structural biology data interpretation (X-ray, cryo-EM)
Preferred skills
Experience applying generative AI or large language models to molecular design
Technologies
Python, generative AI, protein structure prediction tools, cryo-EM software, X-ray crystallography analysis tools
Responsibilities
Apply generative AI and predictive ML models to design and prioritize chemical matter; Partner with Medicinal Chemists to translate computational outputs into synthesis priorities; Lead virtual screening campaigns and ADMET predictions; Contribute to building AI/ML model training datasets; Develop computational workflows for team speed and reproducibility; Interpret structural biology data into design strategies
Seniority
Executive Director, hands-on scientific leadership
