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soil and water management, decision-support tools, precision human nutrition, remote sensing, robotics, sensors and variable-rate applications). The successful applicant must demonstrate strong
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position in fall/winter 2026. We are currently not hiring candidates with core interests in physical geography, civil engineering, and remote sensing; there are far better groups in Vienna focusing on
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environmental sustainability by applying machine learning, data science, remote sensing, robotics, and other emerging digital technologies. The position offers opportunities to collaborate with faculty
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environmental sustainability by applying machine learning, data science, remote sensing, robotics, and other emerging digital technologies. The position offers opportunities to collaborate with faculty
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production systems, climate resilience, sustainable soil, water, and nutrient management practices, technological advances such as AI and remote sensing, weed management, crop quality, food safety, and
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learning, knowledge-guided AI, and/or translational applied AI models • digital agriculture including crop modeling and/or digital twins of assorted scales • remote-, proximal- and near-proximal
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– Geospatial Analysis preferred but not required. Knowledge of GIS, GPS and Remote Sensing and experience using ArcGIS. Familiarity of other campus mapping projects preferred. Possess excellent customer