Postdoctoral Fellow, AI/ML Applications for Vaccine

Pfizer

Quick summary

Work type
On-site
Location
Pearl River, NY
Salary
$64,600–$107,600 / yr
Posted
3 days ago
Closes
Jun 29, 2026
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $204k
This role $86k
$42k most similar roles pay here $278k

This role pays less than 99% of similar roles. Most pay $162,000–$246,150 — the shaded band above. At the midpoint, this role pays about $86k versus about $204k for comparable roles.

Based on 240 similar postings.

Employer

About Pfizer

Pfizer Inc. is one of the world''s largest biopharmaceutical companies, researching, developing, manufacturing, and marketing medicines and vaccines across multiple therapeutic areas including oncology, cardiology, and infectious diseases. Industry: Biopharmaceuticals

Pfizer currently has 33 open roles on FindRole.

Listed pay typically runs $124,400–$207,400 across 33 roles with salary data.

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View all roles at Pfizer

At a glance

TL;DR · Postdoctoral Fellow, AI/ML Applications for Vaccine

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Join Pfizer's Research and Development team as an early-career scientist to design, implement, and validate AI-driven models for vaccine strain selection at the intersection of viral genomics and deep learning. You will develop transformer-based architectures and graph neural networks to predict virus evolution, integrate multi-source data to evaluate prospective coverage scores, and utilize interpretation frameworks to identify key features influencing infectious disease burden. Your day-to-day involves rigorous validation through benchmarking, collaboration with interdisciplinary teams, and clear communication of complex findings to both technical and non-technical stakeholders. The role requires a Ph.D. in computational biology or related fields, proficiency in Python and modern ML frameworks like PyTorch and TensorFlow, experience with viral sequence data, and strong hands-on skills in deep learning for biological sequences. Ideal candidates have direct experience with viral evolution modeling and antigenicity data integration, making significant contributions to the field through publications and open-source projects.

Skills

Python PyTorch TensorFlow scikit-learn transformers graph neural networks SHAP viral genomics antigenicity modeling evolutionary forecasting deep learning sequence-based deep learning models multi-source surveillance immunogenicity data vaccine efficacy data model interpretation frameworks statistical modeling regression analysis mixed-effects models viral or microbial sequence data alignment curation longitudinal analysis CI/CD

What you'll do

  • Develop sequence-based deep learning models using transformer or language-model architectures.
  • Integrate multi-source data to compute prospective coverage scores for vaccine strains.
  • Utilize interpretation frameworks to identify key features in virus evolution.
  • Conduct rigorous validation of AI-driven models through benchmarking and fine-tuning.
  • Publish scientific findings while ensuring confidentiality and reproducibility.

What we're looking for

  • Ph.D. in Computational Biology, Bioinformatics, Computer Science, or Machine Learning.
  • Experience designing and implementing complex ML models for sequence data.
  • Proficiency in Python and modern ML frameworks like PyTorch and TensorFlow.
  • Strong hands-on experience with deep learning for viral protein sequences.
  • Ability to integrate multi-source surveillance and vaccine efficacy data.
  • Conduct rigorous validation and fine-tuning of AI-driven models.
  • Clear communication skills for technical and non-technical stakeholders.

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