Interested in biogeography? Want to work in a supportive group? Curious about integrating data on genetics, pollen, and occurrences to understand species’ range shifts across time? Looking for a postdoc with funds dedicated to career development? Come work with us!
Postdoctoral Position, Integrative Modeling of Species Range Shifts, Department of Fisheries and Wildlife, Michigan State University
A postdoctoral research associate position in population genetics and demographic modeling is available in the Department of Fisheries and Wildlife at Michigan State University. The successful applicant will join an established collaborative network of researchers across five institutions (Michigan State University, the Morton Arboretum, the College of Charleston, the Missouri Botanical Garden, Mount Royal University) and contribute to an NSF-funded data integration project focused on quantifying species’ historical range shifts and population sizes using multiple data types (for more information see: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1759759). Although multiple data types contain information on species’ range shifts (i.e., fossil pollen data, occurrence data and ecological niche models, and population genetic data) these datasets do not always result in equivalent inferences (e.g., on the speed of range shifts). This project seeks to integrate these data types in a coherent analytical framework to infer demographic parameters (migration rates, population sizes, etc.), the location of glacial refugia, and the pace of post-glacial range movement (see Hoban et al 2019 Ecography). The statistical framework provided by Approximate Bayesian Computation (ABC) is a major component of the integrative modeling approaches we are developing. Our project team currently includes individuals with expertise in Mathematics, Statistics, Ecology, Biogeography, and Population Genetics, and we look forward to welcoming a new collaborator to the project.
Applicants must have a Ph.D. in Genetics, Ecology, Evolutionary Biology, Bioinformatics, or a similar field with demonstrated experience in population genetics and a robust computational skillset. In particular, experience with programming (R, Python, C++), Approximate Bayesian Computation, cluster computing, and analysis of population genomic data is desirable. Other desired qualifications include a strong work ethic, problem-solving and time management skills, and experience communicating scientific results. Applicants should demonstrate an interest in joining an established interdisciplinary research team working at the interface of statistics and ecology, and in contributing to an open-source software development project. This position includes opportunities (and funding) to engage in a wide variety of professional development activities (depending on areas of interest) and to participate in planned outreach efforts associated with this project.
Interested applicants should submit a cover letter, statement of research interests, and contact information for three references via the Careers @ MSU website (job posting #632351): https://careers.msu.edu/en-us/job/503149/research-associatefixed-term. In addition to the materials above, code (e.g., link to a GitHub repository) and writing samples (i.e., one or more recent publications) are also strongly encouraged, and will be considered during review. Questions about the position can be directed to Dr. John Robinson, jdrob@msu.edu. The initial appointment for this position is for a period of one year, with the possibility of renewal for a second year pending satisfactory performance. Start date is no later than July 1, 2020. Review of applications will begin March 15, 2020 and will continue until the position is filled.