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Pfizer: One of the World's Premier Biopharmaceutical Companies

Postdoctoral Research Fellow- Quantitative Systems Pharmacology (4840592_La_Jolla)




Full Time


La Jolla, California, United States


Quantitative Systems Pharmacology (QSP) is a discipline that uses mechanistic mathematical models and disease platforms to enhance the robustness and quality of decision-making from exploratory research through clinical development.
The QSP group at Pfizer is seeking a highly motivated postdoctoral candidate to develop and analyze mechanistic mathematical models that incorporate key signaling pathways underlining treatment response in ER+/HER2- breast cancers, with the goal of improving predictions of therapeutic response for initial clinical trials of breast cancer patients. This Postdoctoral Fellowship is an opportunity to work within a dynamic group who are at the forefront of the application of mechanistic systems 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 analyze mathematical models of targeted therapeutics in breast cancer that integrate biological knowledge and available data from Pfizer’s preclinical and clinical programs, with the goal of providing tools for pre-clinical to clinical translation, dose selection, and clinical trial design. They will work collaboratively with biologists, clinicians, clinical pharmacologists, pharmacometricians, QSP and nonclinical modelers to improve designs for effective and durable oncology therapies.


The Postdoctoral Fellow will develop and utilize mathematical models toward enhanced quantitative understanding of the mechanisms for tumor resistance based on literature and internal data.

This may include but is not limited to:

• Employing modeling and simulation techniques for predicting oncology treatment outcomes

• 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 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
  • Interest or experience in combining mechanistic models with deep learning frameworks applied to assessment of anti-cancer drug combinations
  • 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, Julia, Python, R, C/C++ 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
  • Team player
  • Excellent communication and writing skills
  • Primary authorship on relevant publications in peer-reviewed scientific journals

Other Job Details:

  • Eligible for Relocation Package: YES
  • Eligible for Employee Referral Bonus: YES
  • Must be eligible to work in the US


Relocation support available

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.

Sunshine Act

Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider’s name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative.

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.

Research and Development