Postdoctoral Fellow, Quantitative Systems Pharmacology Full-time NEW

Quantitative Systems Pharmacology Postdoctoral Fellowship

Quantitative Systems Pharmacology (QSP) is a scientific discipline that applies mechanistic, mathematical models and disease platforms to improve the robustness and quality of decision-making across the drug discovery and development process, from discovery research to clinical development.

The Pharmacometrics and Systems Pharmacology group at Pfizer, together with the Clinical & Translation Biomarkers team, is seeking a highly motivated postdoctoral fellow to develop, advance, and analyze an end-to-end mechanistic QSP model to better understand therapeutic benefits of incretin therapies beyond weight loss and to generate testable hypotheses for novel mechanisms and indications.

The postdoctoral fellow will develop and analyze an end-to-end QSP model that connects incretin pharmacology across tissues to measurable clinical biomarkers and patient-relevant outcomes (e.g., degree of weight loss and nausea tolerability), supporting stronger causal interpretation of trial results and accelerating evaluation of new indications.

The postdoctoral fellow will be jointly mentored by scientists with complementary expertise in QSP and clinical/translational biomarkers and will collaborate closely with colleagues across multiple functions within Pfizer including lab scientists, statisticians, computational scientists and subject-matter experts within evidence generation and integrated biology.

Role Responsibilities

• Identify and integrate relevant data sources for model development, calibration, and validation, including published literature; internal preclinical and clinical study data; clinical biomarker data; and external real-world and multi-omics resources.
• Apply modeling and simulation approaches to predict clinical outcomes, identify novel indications, and provide novel mechanistic insight into incretin therapies.
• Communicate modeling results and strategic insights effectively to scientists from both quantitative and non-quantitative disciplines.
• Serve as primary author on scientific publications and present research findings at internal and external scientific meetings.

Basic Qualifications

• Ph.D. in Applied Mathematics, Mathematical Biology, Chemical Engineering, Biomedical Engineering, Physics, Pharmaceutical Sciences, Pharmacology, or related discipline with strong numerical components focusing on mathematical modeling and simulation.
• No more than 2 years of post-degree experience.
• Training or previous experience in building QSP or differential-equation-based models of biological or physiological pathways/systems.
• Understanding of theory, principles, and statistical aspects of mathematical modeling and simulation, including parameter estimation techniques.
• Knowledge of modeling, simulation software (MATLAB or Julia preferred), and AI agents.
• Willingness to make a minimum 2-year commitment.
• Provide two letters of recommendation prior to interview.
• Successful record of scientific accomplishments evidenced by scientific publications and/or presentations, including at least one first-author publication in a peer-reviewed journal.

Preferred Qualifications

• Enthusiasm for learning new areas of biology and building on a solid foundation of quantitative and computational skills.
• In-depth understanding of ordinary differential equations (ODEs) and how these can be applied in the development of complex models of biological pathways and systems.
• Self-directed with ability to work independently.
• Ability to perform as a team player and collaborate cross-functionally in multiple disciplines.
• Excellent communication and writing skills.

Physical/mental requirements include the ability to perform mathematical calculations and complex data analysis.

Work location assignment: Hybrid. Last day to apply: April 30th, 2026.