Applications are invited for two two-year postdoctoral research positions to join the NIH-funded Center for the Assessment of the Public Health Impact of Tobacco Regulations, with a multidisciplinary and multi-institutional team of collaborators. The project will conduct analyses of the public health impact of tobacco regulations across a range of tobacco-related conditions and policy outcomes. The interdisciplinary team includes epidemiologists, economists, tobacco scientists, applied mathematicians and statisticians (Rafael Meza, David Mendez, Ken Warner, Nancy Fleischer (University of Michigan), David Levy (Georgetown University), Ted Holford (Yale University)).
Postdoc description and desired qualifications
The postdoc will develop and examine simulation models of tobacco use that explicitly consider multiple tobacco-products and multiple disease outcomes.
Desired areas of expertise include: dynamic and complex systems, parameter estimation, computer programming (familiarity with, R, Python, C++, Matlab), statistical analysis, econometrics and epidemiology modeling.
Experience developing mathematical/simulation models to address problems in public health, epidemiology or health outcomes is a plus.
Applicants should have a doctoral degree in Epidemiology, Health Economics, Econometric, Engineering, Applied Mathematics, Mathematics, Statistics, Operations Research or related field.
Compensation (salary and benefits) will be offered according to University of Michigan and NIH guidelines.
The position is available immediately but starting date is negotiable. To apply please submit CV, names of references, and inquiries to Dr Rafael Meza at email@example.com
The University of Michigan offers a vibrant mathematical modeling and complex systems community. Modeling expertise expands across departments including Epidemiology, Health Management and Policy, Complex Systems, Ecology and Evolutionary Biology, Mathematics and Statistics. The School of Public Health is renowned for its cutting-edge research on the applications of mathematical modeling in epidemiology and public health.