Postdoc: Agentic AI for Drug Discovery Modeling

MSD Malaysia; South San Francisco (CA); On-site; USD 82,000 - 92,000; Full time

Benefits offered by this job

Medical

Dental

Vision healthcare

Retirement benefits (401(k))

Paid holidays

Vacation

Compassionate days

Sick days

Job summary

MSD Malaysia’s Research Laboratories in South San Francisco, CA, invites applications for a Postdoctoral Research Fellow in Modeling & Informatics within Discovery Chemistry. The role focuses on applying AI/ML to automate and accelerate predictive modeling workflows in drug discovery, with access to HPC resources and internal data assets.

The successful candidate will design and benchmark AI/ML approaches, publish findings, and collaborate with cross-disciplinary teams.

Qualifications

• Expertise in ML, cheminformatics, or Computational Chemistry.
• Strong publication and presentation record.
• Hands-on Python ML model development and evaluation.
• Experience designing and interpreting computational experiments.
• Strong quantitative and analytical skills.
• Ability to work independently and collaboratively.

Responsibilities

• Design, execute, and interpret research benchmarking AI/ML methods on internal/external drug discovery data.
• Develop and drive independent AI agent projects for drug discovery modeling.
• Refine agentic AI workflows for transparency and robustness.
• Analyze complex drug discovery datasets using statistical and ML tools.
• Present findings at internal forums, conferences, and peer‑reviewed journals.

Skills

Machine Learning

Cheminformatics

Computational Chemistry

Python

Statistical Analysis

Data Interpretation

Independent Work

Communication Skills

Education

PhD in ML / CS / Computational Chemistry / Cheminformatics / Chemical or Biomedical Engineering / Applied Mathematics

Tools

RDKit

PyTorch

MLflow

LangChain

Job description

MSD Malaysia’s Research Laboratories in South San Francisco, CA, invites applications for a Postdoctoral Research Fellow in Modeling & Informatics within Discovery Chemistry. The role focuses on applying AI/ML to automate and accelerate predictive modeling workflows in drug discovery, with access to HPC resources and internal data assets.

The successful candidate will design and benchmark AI/ML approaches, publish findings, and collaborate with cross-disciplinary teams.