Use Your Power for Purpose
At Pfizer, our purpose is to deliver breakthroughs that transform patients' lives. Central to this mission is our Research and Development team, which strives to convert advanced science and cutting-edge technologies into impactful therapies and vaccines. Whether you are engaged in discovery sciences, ensuring drug safety and efficacy, or supporting clinical trials, your role is crucial. You will leverage innovative design and process development capabilities to expedite the delivery of top-tier medicines to patients globally.
What You Will Achieve
In this role, you will:
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.
Here is What You Need (Minimum Requirements)
Ph.D. in Computational Biology, Bioinformatics, Computer Science, Immunology, or a related field. Publication
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.
Bonus Points If You Have (Preferred Requirements)
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.
Additional Information
Relocation support available
Work Location Assignment: Hybrid
Last day to apply: Sunday January 18th, 2026
Relocation assistance may be available based on business needs and/or eligibility.
Sunshine Act
Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider’s name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative.
EEO & Employment Eligibility
Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States.
Pfizer endeavors to make accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email
disabilityrecruitment@pfizer.com
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