Postdoctoral Research Associate, Computational Ecology

Description

A 3-year postdoctoral research associate position focused on eco-evolutionary modeling of bat populations affected by White-Nose Syndrome (WNS) is available with the Computational Ecology Lab at the University of Montana (UM). Funded by a grant from the National Science Foundation Ecology and Evolution of Infectious Disease program (The Bat-Fungi Disease & Evolution Project), the postdoctoral research scientist will focus on the disease system WNS in the United States working with a new computational model for eco-evolutionary epidemiological dynamics across three bat host species. Using this modeling approach, research questions will address how host ecology and evolution, in response to disease and environment, interact to steer disease dynamics on complex changing landscapes. This project will yield a deep understanding of the processes driving disease dynamics and spread by integrating ecological, genomic and epidemiological approaches into a generalizable forecasting model. Understanding the factors affecting pathogen transmission across human-impacted landscapes is essential for future disease control strategies and development.

The postdoctoral research scientist will be part of collaborative international project team between US and UK institutions to model bat evolution and pathogen transmission dynamics in changing landscapes. They will work closely with the US-team leading simulation modeling efforts (Drs. Erin Landguth, Casey Day, UMT) and the UK-team leading the molecular and genomic data analyses (Drs. Orly Razgour, Rhys Farrer, Duncan Wilson, and UK-hired postdoctoral research scientist, University of Exeter). The US-postdoctoral research scientist will also be provided the opportunity for field and lab research working closely with Dr. Julie Weckworth, UMT, as well as state, federal and non-governmental organizations.

The postdoctoral research scientist will have the opportunity to participate in field work, research, teaching, and mentoring activities that will further their career and professional development 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. Conference travel each year has been included in project budgets for this person.

Example tasks, opportunities, and responsibilities for this position are given as follows:

·         Integrate empirical data, statistical algorithms, and predictive models for assessing the impact of landscapes, life history, and disease resistant and environmental-adaptive genes on WNS dynamics and bat host population trends.

·         Assimilation, management and analysis of large complex datasets across a range of disciplines, including epidemiology, ecology, remote sensing, etc.

·         Utilize high-performance computing including the CEL, UM Griz/Hellgate, and CPHR Data and Modeling Core clusters to process and analyze very large datasets.

·         Participate in field research by gathering empirical data on bats and associated fungal pathogen in multiple states across the eastern US.

·         Participate in lab-related activities at UM: fungal extraction, BSL2, qPCR, pathogen genetics.

·         Assist with the development of summer teaching modules focused on coding opportunities for rural and underrepresented high school students.

·         Attend yearly conferences and communicate findings to research partners.

·         Visit the University of Exeter, UK, to work with Dr Orly Razgour on modeling range suitability for bats under environmental change.

·         Publish at least 4 peer reviewed manuscripts from research, and contribute as co-author on at least 4 more manuscripts from this research.

Additional Information

• 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) is available.
• Salary:  $70,000
• Preference will be given to applicants who can start September 2025 at the University of Montana.
• Funding is available for 2-3 years, but is contingent on satisfactory performance on a yearly basis. 

 

Qualifications

• PhD (by start date) with experience in one or more of the following: wildlife biology, disease ecology, landscape/spatial ecology, connectivity, population/landscape genetics, simulation modeling, computational biology, 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 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.

Application Instructions

Screening of applications will begin after the closing date of August 17, 2025, however, applications will continue to be accepted until an adequate applicant pool has been established.

 

·         Letter of Interest – addressing the stated required skills for the position

·         Detailed resume listing education and describing work experience

·         Three (3) professional references - Names and contact information 

 

Applicants are strongly encouraged to contact Dr. Landguth (erin.landguth@umontana.edu) with any questions with ‘EEID postdoc inquiry’ in subject line.

 

The University of Montana is interested in receiving applications from 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.

Equal Employment Opportunity Statement

University of Montana (UM) is an equal opportunity employer.  UM does not discriminate against any applicant on the basis of protected class status as described in UM’s non-discrimination policy and any applicable law.

Reasonable accommodations are provided in the hiring process for persons with disabilities. For example, this material is available in alternative format upon request.

Qualified candidates may request veterans’ or disabilities preference in accordance with state law.

Criminal Background Investigation is required prior to the offer of employment. In accordance with university regulations, finalists for this position will be subject to criminal background investigations.

References: References not listed on the application materials may be contacted; notice may be provided to the applicant. Testing: Individual hiring departments at UM may elect to administer pre-employment tests, which are relevant to essential job functions.

Employment Eligibility: All New Employees must be eligible and show employment eligibility verification by the first date of employment at UM, as legally required (e.g., Form I-9).