Postdoctoral Fellow, Quantitative Systems Pharmacology, Immunogenicity Modeling & Simulation

Pfizer’s purpose is to deliver breakthroughs that change patients’ lives. Research and Development is at the heart of fulfilling Pfizer’s purpose as we work to translate advanced science and technologies into the therapies and vaccines that matter most. You will work across discovery sciences and preclinical and clinical research to apply cutting edge mathematical modeling & simulation capabilities to accelerate and bring the best in class medicines to patients around the world.

Quantitative Systems Pharmacology (QSP) is a discipline that uses mechanistic mathematical modeling and simulation to enhance the robustness and quality of decision-making from exploratory research through clinical development.

We are seeking a highly motivated postdoctoral research fellow to develop mathematical models to evaluate and predict immunogenicity risk for novel therapeutic proteins and other modalities. By integrating information across multiple candidate mechanisms into the modeling framework, the postdoctoral fellow will evaluate specific mechanistic hypotheses and generate novel insights into how these processes influence clinical immunogenicity. Quantitative prediction of undesired immunogenicity to biotherapeutics can streamline candidate selection and de-risk drug development by integrating complementary mechanistic evidence that would be infeasible using other approaches.

This is an exciting opportunity to work within an industry leading, cross-functional team who are at the forefront of the development and application of quantitative systems pharmacology models to address critical uncertainties in drug discovery and development.

The successful candidate will have earned a Ph.D. in Applied Mathematics, Engineering, Statistics, Physics, Pharmaceutical Sciences, or other related discipline and has a demonstrated track record in scientific publication.

The Postdoctoral Fellow will develop and utilize mathematical models toward enhanced quantitative understanding of immunogenicity mechanisms based on published and internal data.

This may include but is not limited to:

• Employing mechanistic mathematical modeling and simulation techniques for immunogenicity risk prediction

• Identifying relevant data (in vitro and in vivo preclinical and clinical study data) for model development, optimization, and validation

• Designing nonclinical experiments aimed towards generating data for model validation and testing of relevant hypotheses

• Effectively communicating model results and outcomes to scientists in both quantitative and non-quantitative disciplines

• Primary authorship on scientific publications and presenting at internal and external scientific meetings.

• Recent Ph.D. (0-3 years) in Applied Mathematics, Mathematical Biology, Chemical Engineering, Biomedical Engineering, Statistics, Physics, Pharmaceutical Sciences or related discipline with strong numerical components focusing on mathematical modeling and simulation.

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

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

• Office-based position with infrequent travel to scientific conferences and/or business meetings

• 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 language/package (MATLAB/Simbiology, Julia, Python, R, C/C++ preferred)

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

• Self-directed with ability to work independently

• Team player

• Excellent communication and writing skills

• Primary authorship on relevant publications in peer-reviewed scientific journals

Relocation support available

Must be eligible to work in the US

Pfizer requires all U.S. new hires to be fully vaccinated for COVID-19 prior to the first date of employment. As required by applicable law, Pfizer will consider requests for Reasonable Accommodations.

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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.