Post Doc Fellow - Immunogenicity Prediction

About the role

The Computational Toxicology group within Nonclinical Drug Safety (NDS) is seeking a Postdoctoral Fellow to advance AI/ML and structure-based approaches for predicting immunogenicity in biologic and peptide therapeutics. The fellowship is publication-oriented, lasts two years, includes strong mentorship and extensive collaboration with cross-functional teams and external academics, and aims to build reusable, well-documented computational capabilities for translational safety assessment.

Key responsibilities

• Curate, integrate and harmonize biological, structural and clinical datasets from public and internal sources into reproducible analysis workflows.
• Develop computational methods for immunogenicity prediction by combining sequence, structural and experimental data.
• Apply structure-based modeling and simulation to characterize biomolecular interactions and conformational behavior relevant to immune recognition.
• Build and benchmark multimodal machine-learning models that combine sequence, structural and tabular data into robust, calibrated predictors.
• Evaluate model performance against established approaches and assess generalizability across therapeutic modalities.
• Contribute to first-author manuscripts and present at internal forums and external conferences.
• Collaborate with computational, biology and experimental scientists and deliver reproducible, well-documented code, analyses and models.

Required profile

• Currently holds a PhD, or receives a Ph.D. no later than spring 2027.
• Ph.D. in computational immunology, computational biology, computational chemistry, structural biology, bioinformatics or a closely related field.
• Strong first-author publication record and excellent scientific communication skills.

Required skills

• Hands-on experience with co-folding models (e.g. AlphaFold2/Boltz2), multimer modeling or related structure-based methods.
• Molecular dynamics simulation and analysis of biomolecular systems and complexes.
• Python and modern deep-learning frameworks such as PyTorch, with version control and reproducibility practices.
• Working knowledge of immunology relevant to immunogenicity prediction (antigen processing and presentation, MHC/HLA biology, CD4+ T-cell recognition, anti-drug antibody responses).
• Comfortable in HPC/GPU and cloud computing environments.

Preferred: experience applying computational methods to immunology or protein science, familiarity with immunoinformatics and peptide modeling, data curation and API workflows, uncertainty quantification and model calibration, and exposure to biotherapeutic developability or protein engineering.

What we offer

• Salary range of $82,000-$92,000, with eligibility for annual bonus and long-term incentives if applicable.
• Medical, dental, vision and other insurance benefits for employee and family, retirement benefits including 401(k), paid holidays, vacation and compassionate and sick days.
• Visa sponsorship available; domestic relocation; travel requirement of 10%.