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data have the potential to rapidly check animals and serve as a tool for farmers, ranchers, and researchers. Current research is being done by PI to automate imaging and spectral data to develop and
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tools and machine learning for advanced image analysis, weed-crop detection, and mapping. Experience in data collection, processing, and interpretation. Strong background in precision agriculture and
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about the application process, please email ORISE.ARS.Southeast@orau.org and include the reference code for this opportunity. Qualifications The qualified candidate should be currently pursuing or have
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and maintain equipment for measuring gas exchange, image and spectral data collection and analysis, and the effect of different turfgrass management options on its visual quality, sustainability and
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spectroradiometers. Ability to apply AI tools and machine learning for advanced image analysis, weed-crop detection, and mapping. Experience in data collection, processing, and interpretation. Strong background in
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Products. A current research project evaluates the role of microbes in texture losses of vegetables during processing and long-term storage. The selected candidate will participate in all aspects
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system. Hardware-in-the loop (HIL) is used to study prototype CASs, developmental control algorithms, and their ability to provide the required maneuvers throughout the flight envelope. Coupled CFD/RBD
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associated performance predictions will be established to represent the full potential of morphing technology given a fully custom design. The result will provide an experimentally characterized prototype
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, Kansas, the research fellow will engineer wet extraction and dry fractionation processes to produce protein concentrates and associated processing products (meals, starch, and flour) from grain legumes and
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, recording data, collecting samples, and processing and conducting various molecular analyses on the collected samples. This will be in both the laboratory and field using modern molecular techniques. Learning