Postdoc Fellow: Immunogenicity AI/ML & Structure Modeling

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

Benefits offered by this job

Medical

Dental

Vision care

Retirement benefits (401(k))

Paid holidays

Vacation

Compassionate and sick days

Job summary

MSD Malaysia seeks a Postdoctoral Fellow to advance AI/ML and structure-based approaches for immunogenicity prediction in biologic and peptide therapeutics. The role emphasizes publication, mentorship, and collaboration, with two-year funding and opportunities to publish first-author work.

The fellow will develop next-generation computational methods, combine protein structure modeling, immunoinformatics, and multimodal machine learning, and contribute to reusable computational capabilities for

Qualifications

• PhD in computational immunology, computational biology, computational chemistry, structural biology, bioinformatics, or related field.
• Strong hands-on experience with structure-based methods and molecular dynamics.
• Proficiency in Python and modern deep-learning frameworks with reproducible coding practices.

Responsibilities

• Curate and harmonize biological, structural, and clinical datasets into reproducible workflows.
• Develop immunogenicity prediction methods integrating sequence, structure, and data.
• Apply structure-based modeling to characterize biomolecular interactions relevant to immune recognition.
• Build multimodal ML models combining sequence, structure, and tabular data.
• Evaluate models and assess generalizability across modalities.
• Publish first-author manuscripts and present at conferences.
• Collaborate across teams and deliver well-documented code and models.

Skills

Co-folding models (AlphaFold2/Bolt2)

Multimer modeling

Molecular dynamics

Python

PyTorch

Git / reproducible coding

Immunology basics

HPC / GPU computing

Education

PhD in computational immunology / related field

Tools

Python

PyTorch

Version control

Biomolecular modeling tools

Job description

MSD Malaysia seeks a Postdoctoral Fellow to advance AI/ML and structure-based approaches for immunogenicity prediction in biologic and peptide therapeutics. The role emphasizes publication, mentorship, and collaboration, with two-year funding and opportunities to publish first-author work.

The fellow will develop next-generation computational methods, combine protein structure modeling, immunoinformatics, and multimodal machine learning, and contribute to reusable computational capabilities for