One Health Forecasting Postdoctoral Associate (# 377074)

a disease-agnostic ecosystem intelligence system that turns wildlife and environmental data into early warning of risks to the health of people, animals, and ecosystems. The position will initially focus on Minnesota, using 21 years of clinical records from The Raptor Center (more than 18,000 birds) as a pilot, where the data are already compiled and preliminary analyses have produced testable hypotheses. It then extends the approach to wildlife-focused data of all kinds, structured and unstructured, and lays the groundwork for application in other regions, including Southeast Asia. The postdoctoral fellow will combine The Raptor Center's records with public and partner datasets to identify patterns consistent with ecosystem disruption, spillover risk, toxic exposure, or emerging wildlife health threats. Early work will test specific hypotheses, including whether the loss of great horned owls to highly pathogenic avian influenza (HPAI) was followed by increases in prey-borne diseases such as tularemia and rabies. Mentored by core project faculty, the fellow will work with state, national, and international wildlife and One Health partners to turn individual data streams into actionable information. Responsibilities 30% Build and harmonize data pipelines Construct a reproducible data pipeline that harmonizes The Raptor Center's clinical records (2004 to the present) with public and partner datasets relevant to ecosystem and wildlife health, and emerging diseases. Integrate diverse data streams, including biodiversity occurrence and survey records (GBIF, eBird, Christmas Bird Count, state wildlife surveys), human and animal disease surveillance data, and climate and Earth observation products (ERA5, Landsat, Sentinel). Expand beyond wildlife clinical records to any wildlife-focused data, structured or unstructured, such as wildlife morbidity and mortality reports (WHISPers), diagnostic and necropsy records, hunter harvest and citizen-science data, and informal event-based sources such as HealthMap, BEACON, and news reports. Implement advanced data-cleaning methods that explicitly address reporting bias, uneven observation effort, and uncertainty across datasets. 40% Develop analytical models and forecasts Test specific hypotheses using The Raptor Center's data and partner datasets, including climate-driven shifts in breeding timing, lead exposure in bald eagles, and the effects of HPAI-related predator loss on prey populations and prey-borne zoonoses. Develop analytical methods for detecting anomalous wildlife or environmental events, attributing likely drivers, and forecasting elevated risk conditions. Build and evaluate spatiotemporal anomaly detection models, environmental suitability models, machine learning forecasting tools, and risk maps. Calibrate models to local baselines to identify consistent hotspots, seasonal risk windows, and reservoir drivers. Design models to output graded alert levels that prompt follow-up investigation and targeted verification steps rather than simple binary alarms. Validate detection methods retrospectively against known events in The Raptor Center's records, such as the 2022 HPAI outbreak and high West Nile virus years, to measure lead time and false-alarm rates. 20% Evaluate and apply AI and large language models (LLMs) Evaluate and design LLM tools to extract structured information from unstructured text sources, starting with The Raptor Center's electronic medical records and extending to field notes, necropsy reports, and outbreak narratives. Standardize terminology across heterogeneous reporting systems, including changes in cause-of-admission coding over time, by linking diverse narrative descriptions to shared, controlled vocabularies. Assemble, manually annotate, and release at least one benchmark dataset of narrative reports to support automated information extraction. Implement rigorous engineering safeguards to ensure LLM outputs are strictly grounded in trusted source data and separated from downstream interpretation steps. 10% Collaborate, prototype, and disseminate Translate validated model outputs into standardized signals and summaries designed for integration into the National Wildlife Disease Database (NWDD), BEACON, and the work of state public health and wildlife agencies. Pilot prototype decision-support tools with operational partners to document trade-offs between early warnings and false alarms. Disseminate findings through the authorship of multiple peer-reviewed publications and presentations at professional conferences. Release well-documented, open-source code and analytical toolkits to ensure workflows can be audited, reused, and adapted to new regions or hazards. Location and Work Environment Hybrid. Work is primarily performed in a computational research environment at the University of Minnesota College of Veterinary Medicine, St. Paul campus, with options for hybrid work configurations, depending on institutional policies. Most work will be in site with one day of telework. The project involves close virtual and in-person collaboration with the Minnesota Department of Health, the Minnesota Department of Natural Resources, and major surveillance initiatives, including Boston University's Center on Emerging Infectious Diseases (BEACON) and the National Wildlife Disease Database. Qualifications Required Qualifications Ph. D. in Veterinary Epidemiology, Ecology, Data Science, Bioinformatics, Environmental Science, or a closely related quantitative field. Demonstrated ability to conduct independent research, including study design, data collection, and advanced statistical or spatial analysis. Strong foundational programming skills (e.g., R, Python) necessary for building reproducible data pipelines and open-source workflows. Excellent communication skills and a proven capability to work effectively within a high-volume, dynamic, potentially ambiguous, and cross-disciplinary team environment. Preferred Qualifications Experience working with large-scale spatial, temporal, or Earth observation datasets (e.g., ERA5, Landsat, Sentinel) and biodiversity repositories (e.g., GBIF, eBird). Demonstrated expertise in machine learning, spatiotemporal anomaly detection, or predictive forecasting. Experience applying Natural Language Processing (NLP) or evaluating Large Language Models (LLMs) for information extraction tasks. A track record of research utilizing or contributing to a One Health approach. Experience with clinical, surveillance, or wildlife clinical records, or with time-series and count-data epidemiology. Familiarity with international wildlife surveillance frameworks or Southeast Asian ecosystems, to support later expansion of the work. Knowledge, Skills, and Abilities Ability to project a positive, professional, and collaborative attitude toward co-workers, supervisors, and institutional partners. Ability to use research time efficiently, maintain data provenance records, and take initiative to respond to shifting project needs. Ability to communicate complex technical, statistical, and modeling concepts clearly in both verbal and written formats to non-technical stakeholders. Physical Requirements Ability to sit or stand at a computer workstation for prolonged periods of time. Fine motor skills and visual acuity necessary for extensive programming, data visualization, and complex statistical modeling. About the Department The Veterinary Population Medicine (VPM) department specializes in population and individual animal medicine focusing on large animals' health and production, biomedical science, and ecosystem and public health. Our faculty members conduct animal and public-health-focused research to better diagnose, treat, and prevent animal disease, as well as diseases that can be transmitted between animals and humans. Faculty provide clinical instruction in medicine, diseases, surgery, production medicine, public health and reproduction of domestic large-animal species and are home to faculty in clinics, epidemiology, veterinary public health, and pathology. Faculty members provide clinical services for animals, diagnostic services to animal owners, and continuing education and extension programs for veterinarians and animal owners. Teaching The Veterinary Population Medicine Department provides clinical instruction in medicine, surgery, production medicine, diagnostics and reproduction of domestic large-animal species and is home to faculty in epidemiology, veterinary public health, and pathology. The department provides residency training in large animal medicine, surgery, pathology, and veterinary public health and preventive veterinary medicine and works with students in the Veterinary Sciences, and Comparative and Molecular Biosciences graduate programs. Research Faculty members conduct animal and public-health-focused research to better diagnose, treat, eliminate and prevent animal disease, as well as diseases that can be transmitted between animals and humans. Service Faculty members provide clinical services for animals in the Leatherdale Equine Center and Large Animal Hospital, as well as diagnostic services to animal owners through the Veterinary Diagnostic Laboratory. They consult with producers and veterinarians in the community, provide continuing education and extension programs for veterinarians and animal owners, and play an active role in the Center for Animal Health and Food Safety, John Fetrow Dairy Education Center, Equine Center, and the Swine Disease Eradication Center. About The Raptor Center Established in 1974 as part of the University of Minnesota College of Veterinary Medicine, The Raptor Center (TRC) shares the same mission of teaching, research and service. TRC cares for over 1,000 birds annually. As an internationally renowned veterinary teaching hospital, TRC trains students and professionals worldwide to become future leaders in raptor medicine and conservation, and conducts multi-disciplinary ecosystem health research. In addition, TRC has a substantial education and outreach program to educate and inspire the public. With the help of raptor ambassador birds, TRC's education team uses innovative methods to reach over 100,000 people annually through a variety of onsite, offsite, and virtual programming. This work is accomplished with a permanent staff of 25 and a cohort of over 300 volunteers. Pay and Benefits Pay Range: $62,232 - $ 65,000 annually; depending on education/qualifications/experience Please visit the Benefits for Postdoctoral Candidates website for more information regarding benefit eligibility. Competitive wages, paid holidays, and generous time off Continuous learning opportunities through professional training Medical, dental, and pharmacy plans Healthcare and dependent care flexible spending accounts University HSA contributions Disability and life insurance Employee wellbeing program Financial counseling services Employee Assistance Program with eight sessions of counseling at no cost How To Apply Applications must be submitted online. To be considered for this position, please click the Apply button and follow the instructions. You will have the opportunity to complete an online application for the position and attach a cover letter and resume or CV. This position will remain open until filled. To request an accommodation during the application process, please e-mail jobcentr@umn.edu . Diversity The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds. The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu Employment Requirements Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment. About University of Minnesota The University of Minnesota, Twin Cities (UMTC) The University of Minnesota, Twin Cities (UMTC), is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation's most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations. At the University of Minnesota, we are proud to be recognized by Forbes as a Best Employer for Company Culture (2026), Best Employer for Women (2023, 2025, 2026), and Best Employer by State (2022-2026). In 2026, we also received Culture Excellence & Industry Awards recognition for employee appreciation and work-life flexibility.