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in learning how the scientific process is used to solve agricultural problems caused by insect pests. Our respective research programs are focused on using cutting-edge techniques to better understand
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management of field plot trials, data collection, and database management. Experience in large data analyses Experience with operation optimization Experience with machine learning, image analysis Experience
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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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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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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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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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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