Pfizer Postdoc Fellow, Quantitative Systems Pharmacology in Cambridge, Massachusetts
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. We are seeking a highly motivated Postdoctoral Fellow to develop and apply QSP models for the in silico evaluation of novel targets and compounds, which may include application to preclinical and clinical study design and mechanistic interpretation of study results. To this end, the Postdoctoral Fellow will work collaboratively in a highly stimulating and multi-disciplinary environment with biologists, clinicians, precision medicine scientists, clinical pharmacologists, pharmacometricians, and QSP and nonclinical modelers. In addition to building computational models, the individual also will have an opportunity to influence experimental designs towards data generation. The successful candidate will have earned a Ph.D. in Applied Mathematics, Engineering, 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 disease mechanisms and/or pharmacological understanding based on literature and in-house data. This may include but is not limited to:
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
Employing modeling and simulation techniques to predict the safety and/or effectiveness of novel targets or pharmacologic agents
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. (0-3yrs) in Applied Mathematics, Engineering, Physics, Pharmaceutical Sciences, or related disciplines with strong background in mathematical, statistical, and numerical methods
Previous experience in building QSP or differential equation based models of biological or physiological pathways/systems is required
Solid foundation in the theory, principles, and statistical aspects of mathematical modeling and simulation, including numerical methods, parameter estimation/optimization, ODEs, and how these can be applied in the development of complex models of biological pathways and systems
Computational fluency and hands-on experience with one or more modeling and simulation packages or programming languages (e.g., MATLAB, R, Julia, SimBiology, C/C++)
Creative and innovative early career scientist with a passion for learning new areas of biology and building on a solid foundation of quantitative and computational skills
Self-directed, independent, and highly-motivated researcher who excels in a collaborative, multi-disciplinary team environment
Excellent oral and written communication skills
Primary authorship on relevant publications in peer-reviewed scientific journals
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