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evidence of feeding/ predation on onion thrips. The second year of this effort will focus on testing the few selected natural enemies (i.e., based on molecular data, we select species with a high proportion
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-based simulation, virtual environments, and AI-enabled control, with direct applications in crop production and environmental management in controlled settings such as greenhouses and vertical farms
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& biofortification and mechanistic studies in nutrition-health associations. Several positions are available at the Texas A&M AgriLife Institute for Advancing Health Through Agriculture (IHA) based on the Texas A&M
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with process-based models, including APEX, SWAT, EPIC, DayCent, or DNDC. Proficiency in computer programming, including scripting in Python, Fortran, or other computing tools for data processing and
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Development programs and activities improve knowledge and critical decision-making skills related to agriculture, health, leadership, technology, and natural resources. Specifically, community and school-based
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Qualifications: Proficient understanding of agroecosystems, watershed hydrology, soil-plant-water relations, and aquatic carbon dynamics. Solid experience with process-based models, including APEX/SWAT
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collecting and analyzing research data, including imagery from unpiloted aerial systems (UAS). Prepare research manuscripts for publication based on modeling and fieldwork results. Assist in the development