Postdoctoral Fellow in AI/ML Applications for Vaccine Research & Development

Pfizer is a leading pharmaceutical company dedicated to delivering breakthroughs that transform patients' lives. They are seeking a Postdoctoral Fellow in AI/ML Applications for Vaccine Research & Development to develop advanced AI and machine learning models for predicting immunogenicity of pneumococcal conjugate vaccines, while collaborating with multidisciplinary teams and publishing scientific findings.

Responsibilities

• Develop advanced AI and machine learning models, including transformer architectures and graph neural networks, to represent molecular features and predict immunogenicity of pneumococcal conjugate vaccines using preclinical and clinical data
• Apply transfer learning to translate predictive models from preclinical to clinical domains and utilize interpretation frameworks (such as SHAP) to identify key molecular motifs for rational vaccine design
• Conduct meta-analyses of large-scale immunogenicity datasets to characterize quantitative relationships between vaccine physical parameters and immunogenicity outcomes
• Harmonize and curate preclinical and clinical datasets to support robust statistical and machine learning analyses
• Engage in active collaboration with multidisciplinary teams, encompassing experts in data science, preclinical analysis, and clinical vaccine research, to advance pneumococcal conjugate vaccines development
• Publish impactful scientific findings while safeguarding confidential data, ensuring clear, transparent reporting of methods and results to facilitate reproducibility and recognition in peer-reviewed journals and conferences

Skills

• Ph.D. in Computational Biology, Bioinformatics, Computer Science, Immunology, or a related field
• Less than 2 years of post-degree experience
• Willingness to make a minimum 2-year commitment
• Successful record of scientific accomplishments evidenced by scientific publications and/or presentations with at least one first-author publication in a peer-reviewed journal
• Demonstrated expertise in machine learning and deep learning, with hands-on experience in developing and validating predictive models for biological or biomedical data
• Proficiency in Python and relevant AI Machine Learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
• Experience with statistical modeling, including regression analysis and mixed-effects models
• Solid understanding of immunology, especially vaccine immunogenicity and conjugate vaccine design
• Strong data management and curation skills, including harmonization of heterogeneous biological datasets
• Excellent scientific communication skills, with a track record of peer-reviewed publications or presentations
• Ability to work across computational and wet‑lab teams, distill complex results for diverse stakeholders
• Prior experience applying graph neural networks, transformer models, or cross-attention mechanisms to biological sequence or molecular structure data
• Familiarity with glycan-focused modeling and representation, including encoding of polysaccharide and protein carrier features
• Experience in translational research bridging preclinical and clinical datasets, especially in vaccine development
• Knowledge of SHAP or similar model interpretation frameworks for feature attribution in complex models
• Hands-on experience with ensemble modeling and transfer learning in biomedical contexts
• Collaborative experience with experimental biologists and vaccine R&D teams
• Familiarity with regulatory and translational aspects of vaccine development

Benefits

• Participation in Pfizer’s Global Performance Plan with a bonus target of 7.5% of the base salary
• 401(k) plan with Pfizer Matching Contributions
• Additional Pfizer Retirement Savings Contribution
• Paid vacation
• Holiday and personal days
• Paid caregiver/parental and medical leave
• Health benefits to include medical, prescription drug, dental and vision coverage

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