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Open nowPosted 3 hours ago

Postdoctoral Fellow - White - Tailed Deer Integrated Population Modeling

Auburn University368 open roles

Where
Auburn University, AL, United States
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Your applicationOpen nowPostdoctoral Fellow - White - Tailed Deer Integrated Population ModelingAuburn University · Auburn University, AL, United States

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The clock on this job

Early applications get read.

13.4% of postings close within 7 days. Measured by our own scanner across the market. Auburn University postings stay open a median of 7 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.6%3 days
  3. 13.4%7 days
  4. 21.6%14 days
  5. 36.2%30 days
  6. 59.0%60 days
This job: posted 3 hours ago

Auburn University median: 7 days open

The posting

Overview

Researchers from Auburn University’s College of Forestry, Wildlife and Environment, in partnership with the Alabama Department of Conservation and Natural Resources (ADCNR), are seeking a postdoctoral researcher to assist with development of a novel white-tailed deer population modeling and management framework. This collaborative project seeks to identify common challenges and questions associated with effective deer management, construct a suite of modeling tools for evaluating management options, and then use those tools to provide actionable and defensible information to agency biologists. The postdoc will work closely with faculty, graduate students, and ADCNR personnel to develop models that integrate heterogeneous data sources (e.g., harvest records, citizen science observations, deer-vehicle collisions) to improve estimates of deer population parameters. The selected candidate will have substantial freedom to explore options for identifying and modeling data sources as long as the ultimate goals of accurately estimating demographic parameters are kept in focus.

The successful candidate must meet eligibility requirements for work in the United States at the time the appointment is scheduled to begin and continue working legally for the term of employment.

The researcher will be supervised by Drs. Jonathon Valente (https://valentelab.auburn.edu/) and Aniruddha Belsare (https://cfwe.auburn.edu/profile/aniruddha-belsare/). The position will ideally begin in the Spring of 2027 and is fully funded for up to 2.5 years at a starting salary of $60,000 plus benefits. Prospective candidates should be highly motivated, interested in quantitative ecology, and have a strong background in ecology, biology, zoology, wildlife management, population modeling, or a related field.

Applications should be received by November 16, 2026. We anticipate a start date of January 1, 2027. Applicants must include a letter of interest, Curriculum vitae, names and full contact information of at least three professional references, and official transcripts (transcripts should show conferral of a Doctorate degree and date of conferral). Only complete applications will be considered.

Responsibilities

  • Aggregate publicly available and privately owned datasets relating to the distribution, population size, and fitness of white-tailed deer in Alabama and the southeastern United States
  • Develop integrated statistical modeling tools for estimating deer population demographic parameters from these heterogeneous data sources
  • Use an agent-based modeling framework to evaluate the robustness of the developed quantitative approaches
  • Contribute to an adaptive monitoring and modeling framework for generating 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 aimed at improving monitoring, modeling, and management of white-tailed deer across the Southeast
  • Assist with transferring information to agency partners in the form of R shiny applications, worksheets, reports, and/or publications.
  • Present findings at regional, national, and international scientific meetings.

Qualifications

  • PhD in Wildlife, Biology, Ecology, Zoology, Statistics, or another closely related field at the time employment begins.
  • Strong communication skills in oral and written English
  • 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.
  • Experience with integrated population modeling, species distribution modeling, Bayesian data analysis, machine learning, artificial intelligence
  • Experience working with agencies to meet applied management priorities

Minimum Knowledge, Skills, and Abilities

  • 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.

Contract Type

Limited Term Why Work at Auburn?

  • Life-Changing Impact: Our work changes lives through research, instruction, and outreach, making a lasting impact on our students, our communities, and the world.
  • Culture of Excellence:We are committed to leveraging our strengths, resources, collaboration, and innovation as a top employer in higher education.
  • We’re Here for You:Auburn offers generous benefits, educational opportunities, and a culture of support and work/life balance.
  • Sweet Home Alabama:The Auburn/Opelika area offers southern charm, vibrant downtown scenes, top-ranked schools, and easy access to Atlanta, Birmingham, and the Gulf of Mexico beaches.
  • A Place for Everyone: Auburn is committed to fostering an environment where all faculty, staff, and students are welcomed, valued, respected, and engaged.

Ready to lead and shape the future of higher education? Apply today! War Eagle!

Equal Opportunity Compliance Statement

It is our policy to provide equal employment and education opportunities for all individuals without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, gender expression, pregnancy, age, disability, protected veteran status, genetic information, or any other classification protected by applicable law. Please visit the Office of Equal Opportunity Compliance's website to learn more.

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