Postdoctoral Fellow – AI/ML and Agentic AI for Drug Discovery

About the role

The Postdoctoral Research Fellow will join the Modeling & Informatics team within Discovery Chemistry at MSD's Research Laboratories in South San Francisco. The role focuses on applying agentic AI to accelerate predictive modeling workflows in drug discovery.

Key responsibilities

• Design, execute, and interpret research benchmarking AI/ML methods on internal and external drug discovery datasets.
• Develop and lead an independent project to create and evaluate AI agent frameworks for drug discovery modeling.
• Refine agentic AI workflows to improve transparency, robustness, and decision‑making.
• Analyze complex drug discovery data using statistical and machine‑learning tools.
• Present findings at internal forums, external conferences, and in peer‑reviewed journals.

Required profile

• Ph.D. (or expected by spring 2027) in Machine Learning, Computer Science, Computational Chemistry, Cheminformatics, Chemical/Biomedical Engineering, Applied Mathematics, or related field.
• Demonstrated expertise in machine learning, cheminformatics, or computational chemistry with a strong publication record.
• Hands‑on experience building, training, and rigorously evaluating ML models in Python.
• Ability to work independently and thrive in a collaborative, multidisciplinary environment.

Required skills

• Python programming
• Machine Learning frameworks (e.g., PyTorch)
• Experiment‑tracking tools (e.g., MLflow)
• Statistical analysis and data interpretation
• Cheminformatics tools (e.g., RDKit)
• Large language models and agentic AI concepts (e.g., LangGraph, LangChain)
• Graph neural networks or chemical foundation models

What we offer

• Salary range $82,000‑$92,000 per year (visible)
• Annual bonus and long‑term incentive eligibility
• Comprehensive health benefits (medical, dental, vision) for employee and family
• Retirement plan including 401(k)
• Paid holidays, vacation, compassionate and sick days