Postdoc: AI/ML Scientist for Drug Discovery & Agentic AI

Merck; South San Francisco (CA); Hybrid; USD 82,000 - 92,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

401(k) plan

Paid holidays & vacation

Sick days

Job summary

Merck in South San Francisco, CA seeks a Postdoctoral Research Fellow in Modeling & Informatics to advancing AI-driven drug discovery. You will access HPC resources, work on agentic AI workflows, and publish results in peer-reviewed venues while collaborating across disciplines.

The role emphasizes independent project design, rigorous ML benchmarking, and contributing to high-impact scientific outputs within a leading pharmaceutical R&D setting.

Qualifications

• PhD in Machine Learning, Computer Science, Computational Chemistry, Cheminformatics, Chemical or Biomedical Engineering, Applied Mathematics, or related field.
• Hands-on experience building, training and evaluating ML models in Python.
• Experience with computational experiments, model benchmarking and data interpretation.

Responsibilities

• Benchmark AI/ML methods across drug discovery datasets.
• Design and drive independent research on AI agent frameworks for modeling.
• Refine AI workflows to improve transparency and robustness.
• Analyze complex drug discovery datasets using statistical tools.
• Present findings in forums, conferences and journals.

Skills

Machine learning

Cheminformatics

Computational chemistry

Python

Statistics

Independent work

Communication

Publications

Experiment design

Education

PhD in ML/CS/chemistry

Tools

PyTorch

MLflow

RDKit

LangGraph

LangChain

Job description

Merck in South San Francisco, CA seeks a Postdoctoral Research Fellow in Modeling & Informatics to advancing AI-driven drug discovery. You will access HPC resources, work on agentic AI workflows, and publish results in peer-reviewed venues while collaborating across disciplines.

The role emphasizes independent project design, rigorous ML benchmarking, and contributing to high-impact scientific outputs within a leading pharmaceutical R&D setting.