Postdoctoral Research Scientist in Community Ecology and Evolutionary Modeling

The University of Montana is hiring a Postdoctoral Research Scientist in Community Ecology and Evolutionary Modeling to develop a computational model addressing climate change vulnerability in predator-prey systems. The role involves collaboration with multiple institutions, fieldwork, research, teaching, and mentoring. The position is full-time, with an annual salary of $70,000, and options for part-time work and remote work are available.
The University of Montana invites applications for a Postdoctoral Research Scientist in Community Ecology and Evolutionary Modeling to begin Spring 2025. Funded by a grant from the National Science Foundation Organismal Response to Climate Change program, the postdoctoral research scientist will focus on a new computational model for community ecology and evolutionary dynamics to assess climate change vulnerability in a predator (cutthroat trout; Oncorhynchus clarkii) – prey (tailed frog; Ascaphus spp.) system in US Pacific Northwest streams. Using this integrated modeling approach, research questions will address the relative vulnerability of predators and prey when trophic interactions, climate change sensitivity, and adaptive capacity are considered together in spatially explicit settings. This project will yield a deep understanding of key processes in climate change vulnerability and provide novel tools for the integrated assessment of environmental, ecological, and evolutionary components of organismal responses to climate change.

The postdoctoral research scientist will be part of collaborative and interconnected teams across many institutions spanning genomics, physiology, community and ecosystem ecology, eco-evolutionary modeling, and stakeholder engagement. They will work closely with Colorado State University (Dr. Chris Funk), USGS (Dr. Jason Dunham), University of Idaho (Dr. Paul Hohenlohe), USFS (Dr. Alex Fraik), Oregon Dept Fish & Wildlife (Dr. K Anlauf-Dunn), and University of Montana (Dr. Erin Landguth).

The postdoctoral research scientist will have the opportunity to participate in field work, research, teaching, and mentoring activities that will further their career training. They will serve as lead author on peer-reviewed publications; participation in manuscript review; dissemination results at regional, national and international conferences; and participation in seminar series and outreach events. Example tasks, opportunities, and responsibilities for this position are given as follows:

The University of Montana is an Affirmative Action/Equal Opportunity employer and has a strong institutional commitment to the principle of diversity in all areas. In that spirit, we are particularly interested in receiving applications from a broad spectrum of qualified people who would assist the University in demonstrating its five priorities for action: Place student success at the center of all we do; drive excellence and innovation in teaching, learning, and research; embody the principle of “mission first, people always"; partner with place; and proudly tell the UM story.

Position is full-time, 1.0 FTE, Letter of Appointment and includes a comprehensive and competitive benefits package including insurance package, mandatory retirement plan, partial tuition waiver, and wellness program.

The option for part-time work (0.75 FTE) and/or remote work is available.

Salary for this position is $70,000 per year.

Funding is available for 2 years, but is contingent on satisfactory performance on a yearly basis.

Examples of Duties and Responsibilities
• Integrate empirical data, statistical algorithms, and predictive models for assessing the impact of landscapes, life history, and climate-adaptive genes on predator-prey dynamics.
• Test predictions with a predator-prey multispecies spatially explicit, individual-based, eco-evolutionary modeling framework.
• Utilize high-performance computing including the CEL, UM Griz/Hellgate, and CPHR Data and Modeling Core clusters to process and analyze very large datasets.
• Publish at least 2 first-authored peer reviewed manuscripts from research, and contribute as co-author on additional manuscripts from this research.
• PhD (by start date) with experience in one or more of the following: wildlife biology, landscape/spatial ecology, connectivity, population/landscape genetics, simulation modeling, or other related experience.
• Experience in data analysis, modeling and statistical analysis.

Preferred Qualifications
• Coding proficiency in one or more of the following languages: R, Python, C , Java, etc.
• Experience with HPC cluster and Cloud computing.
• Expertise in GIS and the processing/analysis of remotely sensed data and familiarity with large data repositories (e.g., Google Earth Engine).
• Expertise with CDMetaPOP or in the application and interpretation of spatial statistical models and spatio-temporal modeling, individual-based modeling, and machine learning models.
• Record of research output in high quality publications.