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the model development process and publish findings in peer-reviewed journals. Performs other duties assigned. Required Education and Experience: Ph.D. in Agricultural Engineering, Civil and Environmental
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, mineral, or biochemical analysis. •Use analytical equipment (pH meters, CO2 sensors, soil/root/plant sensors, chlorophyll fluorescence, etc.) and process samples using standard laboratory analytical
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a focus on the effect of physical activity on mental health outcomes under the mentorship of Dr. Chad Rethorst. The successful candidate will join a cohort of Postdoctoral Research Associates within
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for greenhouses and vertical farming systems. The successful candidate will focus on robot hardware development, automation system design, machine vision, and intelligent control, supported by physics-based
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Type Staff Job Description Major/Essential Duties of Job: 1. Develop machine learning or physical based models for plant water stress quantification. 2. Develop machine learning models for crop mapping
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, mineral, or biochemical analysis. •Use analytical equipment (pH meters, CO2 sensors, soil/root/plant sensors, chlorophyll fluorescence, etc.) and process samples using standard laboratory analytical
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make a difference in the world! Position Information The selected candidate would assist a team of ecosystem modeling scientists to perform process-based ecosystem models based research and develop
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. Physical activities, including extensive fieldwork, travel, heavy lifting, and working in extreme environments, will be required. Perform other duties as assigned. Required Qualifications: Ph.D. in soil
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: -Ph.D. in biological, chemical, or physical sciences Preferred Experience: -Experience in a molecular biology, biochemistry, or structural biology lab Required Special Knowledge, Skills, and Abilities
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influencing soil organic carbon, soil erosion, and nitrogen processes on croplands and pasture lands in the CONUS. Prior solid experience with process-based models, particularly EPIC, FEST-C, or other related