Natural Resources Job Board

Description: We seek an exceptional PhD student to develop spatially explicit decision models for conservation of at-risk species on Department of Defense (DoD) lands. DoD installations serve an essential function as military training grounds and testing sites, providing operational environments necessary for national defense preparedness.  The DoD manages 27 million acres supporting over 500 at-risk species, with military installations serving as critical refuges for imperiled taxa nationwide. The successful candidate will work with an interdisciplinary team to develop decision support tools integrating species distribution modeling, population dynamics, multi-criteria decision analysis, and cost-effectiveness optimization. You'll work directly with DoD scientists, U.S. Fish and Wildlife Service biologists, and installation managers to translate quantitative models into actionable conservation strategies that maximize military training, land utilization, and species conservation outcomes. This research will directly influence million-dollar conservation investments and species recovery planning.

Research encompasses Bayesian statistical modeling, spatial statistics, machine learning applications, multi-objective optimization, and decision support system development. You'll master cutting-edge methods for species distribution modeling, population viability analysis, landscape connectivity assessment, and multi-species conservation planning using large, heterogeneous datasets. The position will primarily involve data analysis and modeling with limited laboratory research and field research.  Mentorship will be provided by James Peterson (USGS/OSU), Derek Dapp (DoD), and Joe Benjamin (USGS).

 

QUALIFICATIONS: The successful applicant should be highly motivated and have an M.S. degree in ecology, wildlife biology, conservation biology, environmental science, applied mathematics, or related quantitative field; expertise in statistical programming (R, Python, or MATLAB); spatial analysis and GIS experience; strong quantitative skills; and excellent verbal and written communicative abilities. Strong interpersonal skills and an ability to work in a team situation are required. Applicants with experience in Bayesian modeling, spatial statistics, species distribution modeling, population dynamics modeling, and multi-objective optimization will be given special consideration. Additional graduate program information can be found at: 

 

Salary: Annual stipend of $32,500, full tuition waiver, health insurance included.

Closing Date: Until filled. Selection will be made by December 2025.

 Contact: Submit single PDF: cover letter (2 pages max), CV, unofficial transcripts, three references, and writing sample to: