Postdoctoral Fellow, Quantitative Systems Pharmacology

Role Summary

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 is seeking a highly motivated postdoctoral fellow to develop, advance, and analyze mechanistic QSP models of the pathophysiology of rheumatoid arthritis (RA). The goal of this work is to support the development of novel therapies and therapeutic combinations. This fellowship offers the opportunity to work within a dynamic, interdisciplinary team at the forefront of applying mechanistic systems models to address key uncertainties in drug discovery and development.

The successful candidate will hold a Ph.D. in Applied Mathematics, Engineering, Physics, Pharmaceutical Sciences, Pharmacy, Immunology or a closely related discipline, with strong quantitative mechanistic modeling background and a demonstrated record of scientific publication.
 

Postdoctoral Fellowship Overview

The postdoctoral fellow will develop and analyze a QSP model of RA that integrates current biological understanding of disease pathophysiology with available preclinical and clinical data. The overarching objective is to create quantitative tools to inform target and combination selection, guide the development of novel therapeutics, and support optimization of clinical trial design.

The postdoctoral fellow will be jointly mentored by scientists with complementary expertise in QSP, discovery immunology, and clinical/translational biomarkers, and will collaborate closely with colleagues across multiple functions within Pfizer.

Role Responsibilities

The postdoctoral fellow will be responsible for developing and analyzing a QSP model of RA using data from the published literature and internal preclinical and clinical programs. Responsibilities include, but are not limited to:

• Applying modeling and simulation approaches to predict the effects of novel therapies and/or target combinations

• Identifying and integrating relevant data sources (preclinical, systems immunology, and clinical) for model development, calibration, and validation

• Designing nonclinical experiments to generate data for model validation and hypothesis testing

• Communicating modeling results and strategic insights effectively to scientists from both quantitative and non-quantitative disciplines

• Serving as primary author on scientific publications and presenting research findings at internal and external scientific meetings

BASIC QUALIFICATIONS

• Ph.D. (0-2 years) in Applied Mathematics, Mathematical Biology, Chemical Engineering, Biomedical Engineering, Physics, Pharmaceutical Sciences, Pharmacy, Immunology, or related discipline with strong numerical components focusing on mathematical modeling and simulation.

• Training or previous experience in building QSP or differential-equation-based models of biological or physiological pathways/systems is required.

• No more than 2 years of post-degree experience.

• Willingness to make a minimum 2-year commitment.

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

PREFERRED QUALIFICATIONS

• Understanding of theory, principles, and statistical aspects of mathematical modeling and simulation, including parameter estimation techniques.

• 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.

• In-depth, hands-on knowledge of modeling and simulation software (MATLAB or Julia preferred).

• Keen interest in learning new areas of biology and building on a solid foundation of quantitative and computational skills.

• 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

Ability to perform mathematical calculations and ability to perform complex data analysis. 
 

NON-STANDARD WORK SCHEDULE, TRAVEL OR ENVIRONMENT REQUIREMENTS

Work Location: Hybrid (live within a commutable distance to Cambridge, MA and requirement to work on-site on average 2.5 days/week) with infre