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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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: Strong background in controlled environment agriculture (e.g., greenhouse or growth chamber research). Experience with experimental design, data collection, and statistical analysis. Experience with sensor
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separation, polymer dosing trials, and lagoon monitoring activities. Operate manure pumps, samplers, sensors, and related field equipment. ●10%: Extension and Outreach Support - Contribute to the development
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models/tools. Experience with large, varied datasets. Experience working with soil, water, and plant sensors and remote sensing technology. Other Requirements: This position requires physical activities
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, and improve prediction accuracy - develop Machine Learning and AI algorithms for crop management, yield predictions and decision support systems - prepare manuscripts for peer-reviewed publications
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for growth, food/feed quality, mineral or biochemical analysis Use analytical equipment (soil/root/plant sensors, chlorophyll fluorescence, etc.) and process samples using standard laboratory analytical
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and training. -Support processing and integration of datasets, including UAV imagery, satellite data, IoT sensor data, and field observations. -Contribute to workflows for AI/ML applications, crop
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of programming or scripting languages such as Python, Fortran, R or others. Experience in remote sensing data analysis and geographic information systems. Experience in machine learning motivated algorithms and
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protected and open field cultivation systems Use lab and field equipment (ICP, HPLC, gas exchange analyzer, soil/root/plant sensors, chlorophyll fluorescence, etc.), data loggers and image processing tools