The Department of Horticulture and the Department of Plant, Soil and Microbial Sciences at Michigan State University (MSU) invite applications for two positions of full‐time, 12-month tenure-system Assistant Professor with 60% research and 40% extension assignment. The position start date is anticipated to be April 1, 2025. This position will be appointed in either the Department of Plant, Soil and Microbial Science or the Department of Horticulture These positions are part of the new Agricultural Climate Resiliency Program, a partnership among MSU, the Plant Coalition, and the Michigan Department of Agriculture and Rural Development aimed at developing solutions to long-term climate- and water-related problems. As part of this program, MSU has launched an extensive cluster hire process to attract expertise in critical areas of research and outreach necessary to address such grand challenges. These positions are part of a well-established plant and soil science research and extension team, as well as a network of extension educators across the state. Position 1: Life cycle assessment of agricultural systems. The position focuses on filling knowledge gaps in life cycle assessment of agricultural, landscape systems, and/or the built environment by conducting innovative hypothesis-driven research and extension through quantifying environmental impacts, especially climate change across multiple scales. The research will evaluate the impact of weather, soil, and agricultural practices across the diversity of Michigan agricultural commodities and landscapes. Research topics could include understanding organic matter- and microbiome-interactions in soils, carbon sequestration, organic chemical persistence and reactivity, and/or the life cycle analysis of diverse agricultural production and best management practices (including agriculture in built environment and low impact development). The position will develop a forward-thinking extension program and lead the development of educational materials, tools, and presentations to inform and advise farmers, extension educators, industry advisors, governmental and elected officials. Relevant fields could include, but are not limited to, agronomy, horticulture, ecological economics, soil and plant sciences, industrial ecology, and engineering. Goals are to computationally assess environmental impacts of carbon storage in soils and greenhouse-effect gas emissions, intersect with economic analyses, inform management practices and policy, and to engage stakeholders in ways to influence the adoption of new ideas across the agricultural industry. Applicants that leverage machine learning, neural networks and/or artificial intelligence approaches are encouraged to apply. Position 2: Geospatial climate modeling of agricultural systems. The successful candidate will conduct research and extension to develop and implement geospatial models, across multiple scales, that integrate the analysis of remote sensing data, vegetation data, climate data, soil-sensor data, and other relevant spatial datasets to conduct innovative hypothesis-driven research, including assessing the effectiveness of climate smart management practices in agricultural and/or landscape settings. The position will develop a forward-thinking extension program and lead the development of educational materials, and presentations to inform and advise farmers, extension educators, industry advisors, governmental and elected officials. Relevant research could include, but is not limited to, construction and analysis of detailed spatial maps depicting land cover, soil health, vegetation health, terrestrial water cycles, carbon sequestration, greenhouse-effect gas emissions, soil nutrient dynamics, and other relevant variables to monitor the progress and outcomes of new management technologies. The results will inform financial incentive systems and provide toolboxes through the candidate’s extension program to educate stakeholders and policy makers about outcomes and return on investment that will favorably influence change across the agricultural industry. Applicants that leverage machine learning, neural networks and/or artificial intelligence approaches are encouraged to apply.