Postdoc Fellow: AI/ML Immunogenicity & Structure Bio

Merck; West Point (PA); On-site; USD 82,000 - 92,000; Full time

Job summary

Merck is seeking a Postdoctoral Fellow in the Computational Toxicology group within Nonclinical Drug Safety to advance AI/ML and structure-based immunogenicity prediction for biologics and peptides. The role emphasizes publication, collaboration, and reusable computational capabilities for translational safety assessment.

You will develop next-generation methods combining protein structure modeling, immunoinformatics, and multimodal ML, publishing first-author work and presenting at conferences

Qualifications

• PhD in computational immunology, computational biology, computational chemistry, structural biology or related field.
• Strong hands-on experience with structure-based modeling and multimer modeling.
• Proficiency in Python and modern deep-learning frameworks (e.g., PyTorch).
• Experience with immunology concepts relevant to immunogenicity prediction.

Responsibilities

• Curate and harmonize biological, structural, and clinical datasets into reproducible workflows.
• Develop methods for immunogenicity prediction by integrating sequence, structure, and experimental data.
• Apply structure-based modeling and simulation to characterize molecular interactions related to immune recognition.
• Build multimodal ML models combining sequence, structure, and tabular data for predictors.
• Evaluate models against benchmarks and publish first-author work.
• Collaborate with cross-functional teams and deliver reusable, well-documented code and analyses.

Skills

Python

PyTorch

AlphaFold2

Multimodal ML

Structure-based modeling

HPC/GPU

Immunology basics

Data integration

Education

PhD in computational immunology

PhD in computational biology

PhD in bioinformatics

Tools

Git

Linux

Job description

Merck is seeking a Postdoctoral Fellow in the Computational Toxicology group within Nonclinical Drug Safety to advance AI/ML and structure-based immunogenicity prediction for biologics and peptides. The role emphasizes publication, collaboration, and reusable computational capabilities for translational safety assessment.

You will develop next-generation methods combining protein structure modeling, immunoinformatics, and multimodal ML, publishing first-author work and presenting at conferences