Postdoc: Immunogenicity AI/ML & Structural Modeling

MSD Malaysia; Northern (KY); Hybrid; USD 82,000 - 92,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) retirement plan

Paid holidays

Vacation

Compassionate and sick days

Job summary

Merck & Co., Inc. is seeking a Postdoctoral Fellow in the Computational Toxicology group to advance AI/ML and structure-based approaches for immunogenicity prediction in biologic and peptide therapeutics.

The role emphasizes publication, mentorship, and cross-functional collaboration across computational biology and experimental teams. The fellow will curate diverse datasets, develop multimodal models, perform structure-based analyses, and contribute to first-author manuscripts and conferences

Qualifications

• PhD required or to be conferred by Spring 2027.
• Experience with structure-based modeling and multimer modeling.
• Strong programming skills in Python and ML frameworks.
• Familiarity with immunology concepts relevant to immunogenicity prediction.

Responsibilities

• Curate and harmonize biological, structural and clinical datasets.
• Develop immunogenicity prediction methods combining sequence, structure, and experimental data.
• Apply structure-based modeling and MD simulations to biomolecular interactions.
• Build and benchmark multimodal ML models with sequence, structure and tabular data.
• Publish first-author manuscripts and present at conferences.

Skills

Biological Data Analysis

Biology

Biomolecular Interactions

Computational Biology

Immunology Research

Machine Learning

Programming Languages

Protein Analysis

Protein Interactions

Scientific Presentations

Education

PhD in computational immunology/computational biology/computational chemistry/structural biology/bioinformatics

Tools

Python

PyTorch

Git/Version control

HPC/GPU computing

Job description

Merck & Co., Inc. is seeking a Postdoctoral Fellow in the Computational Toxicology group to advance AI/ML and structure-based approaches for immunogenicity prediction in biologic and peptide therapeutics.

The role emphasizes publication, mentorship, and cross-functional collaboration across computational biology and experimental teams. The fellow will curate diverse datasets, develop multimodal models, perform structure-based analyses, and contribute to first-author manuscripts and conferences