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Pfizer · 3 weeks ago

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

United States - New York - Pearl River

Full-time

Hybrid

New Grad, Entry Level

$63K/yr - $104K/yr

0+ years exp

Pfizer is a leading biopharmaceutical company dedicated to delivering breakthroughs that transform patients' lives. In this role, you will develop advanced AI and machine learning models for vaccine research, collaborating with multidisciplinary teams to enhance vaccine development processes.

BiotechnologyHealth CareMedicalPharmaceuticalPrecision Medicine

No H1B

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

Qualification

Machine LearningDeep LearningPythonImmunologyPredictive ModelingStatistical ModelingData ManagementScientific CommunicationCollaboration

Required

Ph.D. in Computational Biology, Bioinformatics, Computer Science, Immunology, or a related field

Successful record of scientific accomplishments evidenced by scientific publications and/or presentations with at least one first-author publication in a peer-reviewed journal

No more than 2 years of post-degree experience

Willingness to make a minimum 2-year commitment

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