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Postdoctoral Fellow

Michigan State University, Department of
Fisheries and Wildlife; and National Wildlife Research Center, USDAAPHIS-Wildlife Services
Job Field:
Job Type:
Full Time
Location Detail:
Fort Collins
Job Description:

The successful candidate will work in collaboration with scientists from Michigan State University, Department of Fisheries and Wildlife (MSU-FW) and USDA-APHIS out of the National Wildlife Research Centre (NWRC) in Fort Collins, CO. The MSU scientist (PI: Dr. Henry [Rique] Campa III) works on wildlife habitat ecology and ecosystem management, with an emphasis on wildlife-habitat interactions and the effects of disturbance on species, populations, and communities. The NWRC scientists (PIs: Dr. Kim Pepin and Dr. Kurt VerCauteren) are applied quantitative disease ecologists with emphasis on understanding spatial processes of disease spread for risk assessment and control.

As part of a broader collaboration with researchers from USDA-APHIS-Veterinary Services, and managers and veterinarians from the Michigan Department of Natural Resources(MDNR), we aim to provide methods and insight for eliminating bovine tuberculosis (bTB) in Michigan. This is an excellent opportunity to develop a framework for understanding and managing spillover at the wildlife-livestock interface that will be applied in practice. The candidate will gain experience in working on a collaborative team with managers and researchers while expanding their skills in quantitative ecology and the scope of their professional networks. The postdoctoral fellow is expected to:

1) Develop risk maps of bTB occurrence in free-ranging white-tailed deer and transmission at the wildlife-livestock interface using bTB surveillance and host demographic data from deer and cattle.

2) Develop data-based models to predict effects of different spatial vaccination strategies in either or both host species on elimination probability and rate.

3) Develop mechanistic transmission models of bTB in deer that consider animal space use in real landscapes and use the models to evaluate effectiveness of alternative control measures (e.g., habitat manipulation, biosecurity measures) alongside vaccination strategies.

4) Collaborate with research team members and natural resources managers from the USDA, MSU-FW, and the MDNR to meet the project goals.



1. Ph.D. degree by the start date of the position in a pertinent biological, physical, or computer science field with demonstrated experiences working on applied ecological problems.

2. Strong record of productivity and publication.

3. Demonstrated competency in statistical modeling.

4. Demonstrated abilities to work independently and on a collaborative, diverse team.

5. Proficiency with a programming language (e.g., R, C++, Matlab,) and experience manipulating, cleaning, and linking diverse data streams.


1. Experience in spatial disease modeling; particularly in assessing effects of control measures on spatial disease transmission.

2. Experience extracting and manipulating GIS and GPS data.

3. Experience with animal movement modeling or spatial processes.

4. Experience in analyzing large datasets.

5. Experience working in collaborative research settings.

6. Experience submitting manuscripts, publishing articles and presenting research findings to professional and lay audiences.


For inquiries or questions, please contact Dr. Rique Campa ( and/or Dr. Kim Pepin ( via e-mail with “bTB Modeling Postdoc” in the subject line.

How to Apply:

Applicants should create a single document (Word or pdf) that includes a letter of interest that highlights the desired attributes specified in the job description, CV/resume, unofficial transcripts, and a list of three references and their contact information. The name of the file should contain the last and first name of the applicant (e.g., Doe.Jane.pdf). The letter of interest should include a statement of the applicant's areas of interest regarding ecological research on spatial disease ecology and/or control of disease in wildlife or at the wildlifelivestock interface, including the applicant's perception of the most important research questions in this discipline, the connections between these areas of research and the applicant’s prior work, and an account of the applicant’s skills in statistics, modelling, and other pertinent quantitative methods.

For full consideration submit application to search posting 689873. Material review will begin February 15, 2021. Position opened until filled.