Postdoc: AI‑Driven Immunology Scientist

Merck; Cambridge (MA); Hybrid; USD 82,000 - 92,000; Full time

Job summary

Merck in Cambridge, MA invites applications for a Postdoctoral Research Fellow focused on AI-guided functional immunology. The project integrates single-cell transcriptomics, functional genomics, and human organoid models to uncover immunological disease mechanisms and generate experimentally validated insights.

You will develop perturbation modeling methods, design active-learning strategies, and collaborate across data science, immunology, and translational teams, communicating results through

Qualifications

• PhD in a quantitative field related to computational biology or AI/ML.
• PhD must be completed no later than spring 2027.
• Experience with single-cell omics or biomedical data analysis.
• Proficiency in Python and PyTorch.
• Experience applying deep models to high-dimensional biological data.

Responsibilities

• Advance AI/ML methods connecting single-cell models with perturbation data.
• Develop interpretable, reproducible computational approaches for perturbations in immune cells.
• Design perturbation experiments with experimental groups and map results to models.
• Create active learning and Bayesian optimization strategies for experimental design.
• Evaluate out-of-distribution generalization and model benchmarking.
• Collaborate with data science, immunology, and translational teams.
• Communicate findings via presentations and publications.

Skills

Machine learning

Publications / conference talks

Science communication

Education

PhD in Computational Biology / Bioinformatics / AI-ML / CS / Immunology

PhD by Spring 2027

Tools

Python

PyTorch

Job description

Merck in Cambridge, MA invites applications for a Postdoctoral Research Fellow focused on AI-guided functional immunology. The project integrates single-cell transcriptomics, functional genomics, and human organoid models to uncover immunological disease mechanisms and generate experimentally validated insights.

You will develop perturbation modeling methods, design active-learning strategies, and collaborate across data science, immunology, and translational teams, communicating results through