Post-Doctoral Research Associate - UT School of Natural Resources (UTIA)
Knoxville, Tennessee
Employer: University of Tennessee
Industry:
Salary: Competitive
Job type: Full-Time
Post-Doctoral Research Associate
UT School of Natural Resources
The national SARS-CoV-2/cervid Targeted Surveillance Team (www.targeted surveillance.com) is seeking a post-doctoral researcher. The Team's overarching objective is to uncover the ecological conditions that generate spatial hotspots of SARS-CoV-2 transmission and persistence in free-ranging cervids. We are particularly excited about recruiting individuals with strong interests in interdisciplinary disease ecology and specific skills in spatial ecology, animal movement modeling, statistics, epidemiological modeling, and population modeling. The Team will use movement and disease data across deer populations in the United States to i) develop new methods for movement-driven modeling of spatio-temporal infection risk ii) build and analyze movement-explicit epidemiological models to generate environmentally and behaviorally informed spatial maps of SARS-CoV-2 transmission potential and iii) use predicted transmission potential to identify shared drivers of SARS-CoV-2 spread and persistence across white-tailed deer populations. The work will be in collaboration with a broader team of researchers from seven universities collecting SARS-CoV-2 surveillance data in wildlife and the USDA, Wildlife Services, National Wildlife Research Center. The finalist will have the opportunity to interact closely with the multi-disciplinary team of movement, disease, and wildlife ecologists, and will be expected to write manuscripts for academic journals, participate in regular collaboration meetings, and present results at meetings and academic conferences.
Qualifications:
REQUIRED QUALIFICATIONS: PhD in ecology, epidemiology, statistics, movement ecology, population ecology, spatial ecology, mathematical biology, or other similar fields. Demonstrated experience building and analyzing mathematical and statistical models aimed at answering biological, ecological, or epidemiological questions and a publication record in peer reviewed journals. Demonstrated experience with programming languages R, Python, Matlab, or similar.
COMPENSATION AND TIMELINE: This is an exempt, regular, full benefits position, with grant funding secured for an initial period of one year and offers a competitive salary. This position is based at the University of Tennessee, Knoxville, though remote work will be considered. Application Deadline: August 9, 2024; hire date negotiable. The UT School of Natural Resources is committed to providing a safe and welcoming environment for all. Women and minorities are encouraged to apply.
TO APPLY: Submit a one-page cover letter summarizing research interests and experience with mathematical modeling, a curriculum vitae, copies of academic transcripts, and full contact information of three professional references. Review of applications will begin as soon as possible and will end when a suitable candidate is identified. Questions regarding the position may be directed to Dr. Mark Wilber (mwilber@utk.edu).
UT School of Natural Resources
The national SARS-CoV-2/cervid Targeted Surveillance Team (www.targeted surveillance.com) is seeking a post-doctoral researcher. The Team's overarching objective is to uncover the ecological conditions that generate spatial hotspots of SARS-CoV-2 transmission and persistence in free-ranging cervids. We are particularly excited about recruiting individuals with strong interests in interdisciplinary disease ecology and specific skills in spatial ecology, animal movement modeling, statistics, epidemiological modeling, and population modeling. The Team will use movement and disease data across deer populations in the United States to i) develop new methods for movement-driven modeling of spatio-temporal infection risk ii) build and analyze movement-explicit epidemiological models to generate environmentally and behaviorally informed spatial maps of SARS-CoV-2 transmission potential and iii) use predicted transmission potential to identify shared drivers of SARS-CoV-2 spread and persistence across white-tailed deer populations. The work will be in collaboration with a broader team of researchers from seven universities collecting SARS-CoV-2 surveillance data in wildlife and the USDA, Wildlife Services, National Wildlife Research Center. The finalist will have the opportunity to interact closely with the multi-disciplinary team of movement, disease, and wildlife ecologists, and will be expected to write manuscripts for academic journals, participate in regular collaboration meetings, and present results at meetings and academic conferences.
Qualifications:
REQUIRED QUALIFICATIONS: PhD in ecology, epidemiology, statistics, movement ecology, population ecology, spatial ecology, mathematical biology, or other similar fields. Demonstrated experience building and analyzing mathematical and statistical models aimed at answering biological, ecological, or epidemiological questions and a publication record in peer reviewed journals. Demonstrated experience with programming languages R, Python, Matlab, or similar.
COMPENSATION AND TIMELINE: This is an exempt, regular, full benefits position, with grant funding secured for an initial period of one year and offers a competitive salary. This position is based at the University of Tennessee, Knoxville, though remote work will be considered. Application Deadline: August 9, 2024; hire date negotiable. The UT School of Natural Resources is committed to providing a safe and welcoming environment for all. Women and minorities are encouraged to apply.
TO APPLY: Submit a one-page cover letter summarizing research interests and experience with mathematical modeling, a curriculum vitae, copies of academic transcripts, and full contact information of three professional references. Review of applications will begin as soon as possible and will end when a suitable candidate is identified. Questions regarding the position may be directed to Dr. Mark Wilber (mwilber@utk.edu).
Created: 2024-08-22
Reference: 2400000163
Country: United States
State: Tennessee
City: Knoxville
ZIP: 37918
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