Postdoctoral Scientist – AI & Machine Learning for Predictive Drug Absorption

Pfizer

Postdoctoral Scientist role in AI & Machine Learning for Predictive Drug Absorption at Pfizer. Focused on building predictive models and collaborating in a multidisciplinary environment.

Posted 6/16/2026full-timeGroton • Connecticut, Massachusetts • 🇺🇸 United StatesJuniorMid-Level💰 $64,600 - $107,600 per yearWebsite

Tech Stack

Tools & technologies

PythonPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

Design, train, and evaluate machine-learning models for predicting oral drug absorption–related outcomes from high-dimensional datasets.
Develop end-to-end ML pipelines, including data ingestion, feature engineering, model training, validation, and performance benchmarking.
Work with large, diverse datasets, including experimental biopharmaceutics data and clinical pharmacokinetic datasets, and internally generated datasets relevant to predictive modelling.
Apply and compare a range of ML approaches, including tree-based methods, neural networks, surrogate models, probabilistic approaches for uncertainty-aware prediction.
Focus on model interpretability and explainability, linking learned patterns to scientifically meaningful drivers where possible.
Quantify model robustness, generalizability, and uncertainty, particularly in data-sparse or extrapolative scenarios.
Translate ML outputs into actionable insights for drug development teams, rather than purely academic metrics.
Communicate results through internal technical reports, cross-functional presentations, and peer-reviewed publications.
Contribute to the establishment of AI-enabled predictive platforms within Pfizer R&D.

Requirements

What you’ll need

PhD in Machine Learning, Data Science, Applied Mathematics, Computational Sciences, Engineering, Pharmaceutical Sciences, or a closely related quantitative discipline.
Provide two letters of recommendation with your application (e.g. professors/PI).
Willingness to commit to the fixed-term full-time postdoctoral fellowship (duration: 2–4 years).
Less than 2 years post-doctoral experience.
At least 1 first-author scientific research article in high-quality specialty or general readership journals.
Strong foundation in machine learning and statistical modelling, with hands-on experience building and evaluating predictive models.
Proficiency in Python and/or R for data analysis and ML development (e.g. scikit-learn, PyTorch, TensorFlow, or similar).
Experience working with large, heterogeneous datasets and structured scientific data.
Demonstrated research productivity, evidenced by peer-reviewed publications or equivalent scientific outputs.
Ability to collaborate effectively in multidisciplinary research environments.

Benefits

Comp & perks

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 including medical, prescription drug, dental and vision coverage

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningpredictive modelingstatistical modelingdata analysisfeature engineeringmodel trainingmodel validationmodel interpretabilitymodel robustnessuncertainty quantification

Soft Skills

collaborationcommunicationresearch productivitycross-functional teamwork

Certifications

PhD in Machine LearningPhD in Data SciencePhD in Applied MathematicsPhD in Computational SciencesPhD in EngineeringPhD in Pharmaceutical Sciences