Pfizer Postdoctoral Fellow, Systems Modeling in Cambridge, Massachusetts
Please be sure to submit your cover letter and/or research summary in addition to your CV when applying for this position
The Quantitative Systems Pharmacology (QSP) Lab in Pfizer's Internal Medicine Research Unit (IMRU) is responsible for developing insights to help advance IMRU clinical candidates; identifying and evaluating promising new therapeutic targets through physiologically-based modeling and simulation; and analysis and interpretation of preclinical and clinical data. We seek a highly motivated postdoctoral candidate to develop and analyze mechanistic, mathematical models of cardiac and skeletal muscle mitochondria metabolism to enable the in silico testing of mechanistic hypotheses of metabolic inflexibility with the ultimate goal of improving the identification and evaluation of therapeutic targets for heart failure (HF) and type 2 diabetes mellitus (T2DM).
In addition to enabling in silico identification and assessment of T2DM and HF drug targets, the successful candidate will pursue new avenues for professional development in areas of QSP and MFA modeling, cellular biophysics, data analysis, and uncertainty quantification. The project would involve close interaction with the experimental groups, helping to improve design of metabolic flux analysis (MFA) studies to understand and quantify the contribution of different substrates. The mechanistic insights gained from detailed analyses of the in silico model will generate physiological hypotheses that may be tested experimentally and/or in the clinic. The expectation is that the resulting findings will lead to improved confidence in rationale for the pursuit of novel agents for the treatment of T2DM and HF.
Develop validated mathematical models of key pathways underlying mitochondria properties; develop and implement numerical methods for parameter estimation and model simulation
Identify, obtain, and organize primary data sets for use in defining parameter values/ranges and for model calibration and validation; contribute to the design of in vitro and in vivo experiments to resolve key knowledge gaps in our understanding of the biology
Generate testable hypotheses regarding the pathogenesis and treatment of T2DM and HF at the level of the mitochondria, based on detailed analyses of model and simulation results
Present novel results internally and at regional, national and/or international meetings
Publish model and simulation results in high-impact journals
Recent Ph.D. (0-3 years) in Engineering, Applied Mathematics, Physics or related discipline with strong numerical components focusing on mathematical modeling and simulation. Training and/or experience in mechanistic modeling of biological or physiological systems is preferred.
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, C/C++ preferred)
Prior knowledge of and/or experience with Metabolic Flux Analysis (MFA) studies is beneficial
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
Excellent communication and writing skills
Primary authorship on relevant publications in peer-reviewed scientific journals
Must be willing to relocate to Cambridge, MA, USA
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