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contamination in corn remains one of the most persistent threats to U.S. agriculture, with significant implications for food safety and crop quality. Current satellite imaging technologies lack ability to detect
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machine learning, image recognition, and prediction of damage to tree nuts from insect pests. They will also collaborate with other team members on statistical analysis of data collected as part of
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about the application process, please email ORISE.ARS.Midwest@orau.org and include the reference code for this opportunity. Qualifications The qualified candidate should be currently pursuing or have
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, testing, and operation; contributing to the design of plant experiments; caring for and harvesting plant materials; collecting and recording measurements; entering and organizing data; and performing basic
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-liquid interface in vitro models of the human lung Gaining experience preparing routine chemical and drug solutions Conducting in-depth analysis of high-throughput data Interpreting fluorescent image
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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 have received a bachelor's or
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using sensors, data loggers, and thermal images Lab experiments examining how nutrition affects performance and physiological traits Field experiments quantifying behavior of insects Mentor(s): The mentor
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Language Processing / Large Language Models, image classification and object detection and Aided/Automated Target Recognition or other applications of interest to the Army to improve warfighting, lethality, and
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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