Dept of Statistics, University of Michigan

Position ID: UniversityofMichigan-POSTDOC [#13766]
Position Title: Postdoctoral research fellow
Position Type: Postdoctoral
Position Location: Ann Arbor, Michigan 48109, United States [map]
Subject Areas: Statistics, Ecology
Application Deadline: 2019/04/14 finished (2019/03/21, finished 2019/04/15, listed until 2019/09/01)
Position Description:    

*** this position has been closed, and no new applications will be accepted. ***

Applications are invited for a postdoctoral research position working on a new NSF/NIH-funded project at the interface of statistics, modeling, and epidemiology aiming to develop powerful new methods for spatiotemporal dynamics and to combat dengue fever. Specifically, the postdoc will be part of an interdisciplinary team working to develop statistical methodology for partially observed spatiotemporal dynamic systems and to use this methodology to infer dynamic models that explain and predict patterns of dengue incidence in Rio de Janeiro. 

The postdoctoral fellow will be jointly supervised by Profs. Edward Ionides (Statistics) and Aaron King (Ecology & Evolutionary Biology, Complex Systems, Mathematics) at the University of Michigan. The project team also includes Prof. Mercedes Pascual of the University of Chicago. These researchers have long experience in methods development, implementation, and application in infectious disease epidemiology and ecology. The University of Michigan consistently ranks among the leading universities worldwide and has top-tier graduate programs in statistics, ecology & evolutionary biology, and epidemiology. Ann Arbor is also routinely rated one of the best places to live in the U.S. due to its affordability, lively culture, and natural beauty. 

Applicants should have a doctoral degree in Statistics, Epidemiology, Ecology, Applied Mathematics, Computer Science, or a related field, a good record of scholarly publication, and excellent written and oral communication skills. 

Compensation and start date. The salary is $53k per year and comes with the standard University of Michigan benefits package. Two years of funding are available, contingent on adequate progress during the first year. The start date is negotiable, with a target of July 2019. 

The University of Michigan is a Non-Discriminatory/ Affirmative Action Employer. Individuals from underrepresented groups are especially encouraged to apply. 

Detailed project summary. Statistical analysis of partially-observed, nonlinear, stochastic spatiotemporal systems is a methodological challenge. Existing inference algorithms suffer from a “curse of dimensionality” that prohibits their applicability to models describing interacting dynamic processes occurring within and between many spatial locations. In this project, new inference algorithms will be developed, and shown in theory and in practice to advance capabilities for spatiotemporal data analysis. Methodological research will be carried out in the context of addressing transmission of dengue virus within a tropical megacity. Global incidence of dengue has risen 30-fold over the past fifty years, with notable geographical expansion in South and Central America. The municipality of Rio de Janeiro is a focal point for dengue transmission in this region. Spatiotemporal data on dengue cases in Rio de Janeiro will be analyzed, together with data on human movement, temperature, and rainfall. Policy decisions for the detection, control, and potential eradication of infectious diseases are best informed by model-based understanding of disease transmission. Improved understanding of the spatiotemporal dynamics of disease transmission will have implications for improvements in disease control. Mathematical models will be developed to describe spatiotemporal dynamics of dengue transmission, and the novel statistical methodology will be used to link these models to the data from Rio de Janeiro.

Application Materials Required:
Submit the following items online at this website to complete your application:
And anything else requested in the position description.

Further Info:
https://lsa.umich.edu/stats
 
The University of Michigan
Department of Statistics
311 West Hall
1085 South University
Ann Arbor, MI 48109-1107

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