Postdoctoral Fellow - White - Tailed Deer Integrated Population Modeling

Auburn University • Auburn, AL

3d

About The Position

Auburn University’s College of Forestry, Wildlife and Environment, in partnership with the Alabama Department of Conservation and Natural Resources (ADCNR), seeks a postdoctoral researcher to develop a white-tailed deer population modeling and management framework. The collaborative project will identify common deer-management challenges and questions, develop modeling tools for evaluating management options, and provide actionable, defensible information to agency biologists. The researcher will work with faculty, graduate students, and ADCNR personnel to integrate heterogeneous data sources—including harvest records, citizen science observations, and deer-vehicle collisions—to improve estimates of deer population parameters. The postdoctoral fellow will have substantial freedom to explore approaches for identifying and modeling data sources while keeping accurate estimation of demographic parameters as the central goal.

The position is supervised by Drs. Jonathon Valente and Aniruddha Belsare. It is fully funded for up to 2.5 years, with a starting salary of $60,000 plus benefits. The position ideally begins in Spring 2027; the anticipated start date is January 1, 2027. Applicants must be eligible to work legally in the United States when the appointment begins and throughout the employment term. Applications should be received by November 16, 2026. Applicants must submit a letter of interest, curriculum vitae, contact details for at least three professional references, and official transcripts showing conferral of a doctorate and its date. Only complete applications will be considered.

Requirements

• PhD in Wildlife, Biology, Ecology, Zoology, Statistics, or another closely related field by the time employment begins.
• Strong oral and written English communication skills.
• Ability to work independently and as part of an interdisciplinary team.
• Self-motivation, a positive attitude, and strong interpersonal skills.
• Experience presenting and publishing peer-reviewed research.
• Experience with the R statistical programming language, GIS software, and population modeling.
• Knowledge of integrated population modeling, species distribution modeling, Bayesian analysis, machine learning, and artificial intelligence.
• Ability to collaborate with agencies and stakeholders to support applied management objectives.
• Eligibility to work legally in the United States when the appointment begins and throughout the term of employment.

Nice To Haves

• Experience with integrated population modeling, species distribution modeling, Bayesian data analysis, machine learning, and artificial intelligence.
• Experience working with agencies to meet applied management priorities.

Responsibilities

• Aggregate publicly available and privately owned datasets on white-tailed deer distribution, population size, and fitness in Alabama and the southeastern United States.
• Develop integrated statistical modeling tools to estimate deer population demographic parameters from heterogeneous data sources.
• Use an agent-based modeling framework to evaluate the robustness of quantitative approaches.
• Contribute to an adaptive monitoring and modeling framework for robust estimates of deer population characteristics and for setting harvest regulations.
• Generate recommendations for future data collection efforts to improve population estimates.
• Contribute to peer-reviewed publications that improve monitoring, modeling, and management of white-tailed deer across the Southeast.
• Help transfer information to agency partners through R Shiny applications, worksheets, reports, and/or publications.
• Present findings at regional, national, and international scientific meetings.

Benefits

• Benefits are offered, described as generous.
• Educational opportunities.
• A culture of support and work/life balance. The position also offers a starting salary of $60,000.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree