Assistant​/Associate Professor in AI for Environmental Modeling​/Forecasting

Details

Global change is rapidly altering the Earth system, leading to more devastating extreme events and a greater need for tools for adaptation and planning. A growing wealth of observational data from satellites, sensor networks, foundation models, gridded weather and reanalysis, socio-economic databases, and other multi-scale technologies are enabling a higher-fidelity view of the Earth system than ever before, but a lack of computational tools limits our ability to leverage these data to understand the complex feedback governing the Earth system and its changes.

The University of Utah, under the leadership of the One-Utah Responsible Artificial Intelligence (AI) Initiative (One-U RAI), is building a new group to address the full range of environmental challenges and opportunities enabled by AI by leveraging, integrating and enhancing existing strengths in earth and environmental science, social science, modeling and computation. We seek candidates who will exploit emerging datasets to advance environmental and Earth system modeling, forecasting, and projection using state‑of‑the‑art computational approaches such as machine vision, digital twins, AI, uncertainty quantification, data assimilation, or fusion techniques, with the goal of improving forecasts, hindcasts and future projections of environmental change.

Methodological strengths may include Earth‑system foundation or other machine‑learned physics models; the use of AI methods for model parametrization; multi‑model and multi‑fidelity ensemble and generative approaches for uncertainty quantification; surrogate (reduced order/digital twin) models; and other modern data‑assimilation and data‑fusion techniques. Envi qualified candidates may have research interests across the globe, and with an interest in developing a research program in Utah and the Intermountain West.

A doctoral degree in environmental or climate science, environmental studies, environmental engineering, applied math, geological science, geography, urban planning, computational science, or related fields is required by July 1, 2026. This tenure‑track position is for an Assistant or Associate Professor level to begin in Fall 2026. The successful candidate will have a research appointment with the SCI Institute at the University of Utah, and their tenure home will be in one of the following participating colleges and departments:
College of Architecture & Planning (Department of City and Metropolitan Planning);
College of Business (Departments of Operations & Information Systems and Quantitative Analysis of Markets and Organizations);
John and Maria Price College of Engineering (Department of Civil and Environmental Engineering);
College of Law;
College of Science (School of Biological Sciences, Departments of Atmospheric Sciences and Geology & Geophysics);
College of Social and Behavioral Science (Schools of Environment, Society & Sustainability and Public Affairs, Departments of Anthropology, Economics, and Sociology & Criminology).

We seek a colleague with a commitment to excellence in teaching and a demonstrated ability to obtain research funding and publish high‑quality peer‑reviewed research. We are especially interested in applicants who can contribute to our university’s Strategy 2030 and the One-U RAI.

• Develop and maintain an ongoing program of scholarly research that involves computational methods and visualization for application within climate modeling and forecasting.
• Develop meaningful collaboration with faculty in SCI, the candidate’s home department, and other academic departments and research centers (e.g., Wilkes Center for Climate Science and Policy, the NSF WIRED Global Center and the Global Change and Sustainability Center) to promote the integration of AI.
• Meet the teaching requirements in the candidate’s chosen academic department.
• Engage as a member of the SCI Institute faculty.
• Train and mentor undergraduate and graduate students.
• Develop and submit research funding proposals to national agencies and foundations.
• Develop partnerships and commercialization opportunities to drive excellence and innovation in AI‑enhanced research.
• Conduct…