US Forest Service · Montana · posted today
Oregon State University (OSU) and the US Forest Service (USFS) are seeking applicants for a one-year postdoctoral scholar position with the Conservation Biology Program at the Institute for Natural Resources at Oregon State University and the Rocky Mountain Research Station with the USFS. Funding is available for an extension of two additional years contingent upon performance. The selected researcher will work with Dr. Tavis Forrester (USFS) and Dr. Sean Matthews (OSU) to conduct grizzly bear research in collaboration with the Interagency Grizzly Bear Committee Science Team. The researcher will use human mobility data in collaboration with Dr. Mark Ditmer of the Rocky Mountain Research Station to evaluate illegal motorized use on closed roads on public land and grizzly bear movement and habitat use in relation to illegal motorized use. The researcher will also work on a review paper that summarizes the literature relating to secure habitat for grizzly bears. Research resulting from this position will inform habitat management for grizzly bears on USFS land throughout grizzly bear range in the contiguous US. The desired starting date for the position is the winter of 2026/2027. Salary for the position starts at $70,000 per year with salary increases each year. The postdoc will work at the Rocky Mountain Research Station lab located on the campus of the University of Montana. Send a cover letter and CV to Tavis Forrester at tavis.forrester@usda.gov to apply. Required Qualifications: • A PhD degree in wildlife biology, ecology, statistics, or similar fields • A record of publishing in peer-reviewed scientific journals. • Proficiency with data analysis and the use of code for data analysis (R, Python, BUGS/JAGS, Stan, etc.) • Ability to communicate and collaborate with research groups • Desire to produce science that is relevant to conservation • Desire and ability to build a positive, team oriented, and safe working environment for all backgrounds and identities. Preferred qualifications: • Experience working with large datasets, data cleaning, and combining data from multiple collaborators • Experience conducting complex statistical analyses including step-selection functions, resource selection functions, and survival analyses using frequentist and Bayesian statistics including generalized linear mixed models, hierarchical models, and/or machine learning models. • Experience collecting and using large scale spatial data (e.g., raster and vector datasets in ArcGIS, R, or Google Earth Engine) for spatial analysis using R, ArcGIS, Google Earth Engine, and/or Python • Experience working with research collaboratives and engaging managers and stakeholders with research results • Experience working with wildlife species whose management may generate controversy
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