Post Doc Fellow-Immunogenicity Prediction

Location: Northern

## Post Doc Fellow-Immunogenicity Prediction Apply:
Not Applicable:
USA
- Pennsylvania
- West Point:
Full time:
Posted Today:
End Date:
October 12, 2026 (11 days left to apply):
R419989
** Job Description
** The Computational Toxicology group within Nonclinical Drug Safety (NDS) seeks a Postdoctoral Fellow to advance AI/ML and structure-based approaches for immunogenicity prediction in biologic and peptide therapeutics. The successful candidate will develop next-generation computational methods combining protein structure modeling, immunoinformatics, and multimodal machine learning to improve prediction of biologically relevant immune responses. This is a publication-oriented, two-year fellowship with strong mentorship and extensive cross-functional and external academic collaboration.

The Fellow will publish first-author manuscripts, present at scientific conferences, and help establish 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 integrating sequence, structural, and experimental data.
* Apply structure-based modeling and simulation approaches 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 scientific presentations at internal forums and external conferences.
* Collaborate with computational, biology, and experimental scientists, and deliver reproducible, well-documented code, analyses, and models.  
*
* Educational Requirements:

*** Must currently hold a PhD OR
* Receive 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.  
** Required

Experience and Skills:

*** Strong hands-on experience with co-folding models (e.g AlphaFold2/Boltz2), multimer modeling, or related structure-based computational methods.
* Experience with molecular dynamics simulation and analysis of biomolecular systems, complexes, or conformational behavior.
* Strong software development skills in Python and modern deep-learning frameworks such as PyTorch, with sound practices in version control, reproducibility, and scientific computing.
* Working knowledge of immunology relevant to immunogenicity prediction, including antigen processing and presentation, MHC / HLA biology, CD4+ T-cell recognition, and anti-drug antibody (ADA) responses.
* Comfort working in HPC / GPU and cloud computing environments.
* Excellent scientific communication skills and a strong first-author publication record.  
** Preferred

Experience and Skills:

*** Experience applying computational methods to immunology, structural biology, or protein science problems.
* Familiarity with antigen processing and presentation, MHC/HLA biology, or related immune recognition concepts.
* Experience with data integration, biological dataset curation, and programmatic workflows using public resources and APIs.
* Familiarity with uncertainty quantification, model calibration, and rigorous benchmarking.
* Familiarity with biotherapeutic develop ability, protein engineering, or related optimization concepts.
* Exposure to immunoinformatics, peptide modeling, or related predictive methods is a plus.
* The salary range for this…