Associate Principal Scientist, AI for Chemical Toxicology
Core
Lead next-generation predictive safety modelling at scale using chemoinformatics, bioinformatics, and AI/ML to deliver decision-shaping safety insights and inform risk assessment and progression decisions in drug development.
Role type
Associate Principal Scientist, AI for Chemical Toxicology
Builds
Predictive safety models, reproducible workflows, and model validation frameworks for drug development.
Domain
Pharmaceutical R&D, Chemical Toxicology, AI/ML
Deliverable
production ML models
Required skills
Chemoinformatics, Bioinformatics, AI/ML (PyTorch, TensorFlow, scikit-learn), Advanced Python or R, Multimodal data integration (chemical descriptors, omics, imaging, NAMs), MLOps/DevOps practices, Scientific leadership, Strategic modelling
Preferred skills
Safety Omics, Cell Painting, imaging data, Toxicology/Pharmacology/ADME background, Cloud computing, Workflow automation, Publications in top AI conferences/journals, Supervising scientists
Technologies
PyTorch, TensorFlow, scikit-learn, GitHub, CI/CD pipelines
Responsibilities
Develop, optimise, and deploy predictive safety models; Create reproducible workflows and data QC procedures; Integrate multimodal biological and chemical datasets; Serve as scientific lead for project teams; Drive innovation and identify strategic modelling opportunities; Lead collaborations with academia and technology partners; Mentor junior scientists
Seniority
Associate Principal, hands-on IC with strategic influence
