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improving plant health using machine learning and artificial intelligence. Mentor(s): The mentor for this opportunity is Yulin Jia (yulin.jia@usda.gov ). If you have questions about the nature of the research
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. Under the direction of cognizant Federal personnel, participating researchers have opportunities to learn how to lead tasks, explore new research areas for DHS, and participate in networking opportunities
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. Under the direction of cognizant Federal personnel, participating researchers have opportunities to learn how to lead tasks, explore new research areas for DHS, and participate in networking opportunities
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and often different from the canonical types of data used to benchmark machine learning (ML) algorithms. In this opportunity, we will be evaluating how state-of-the-art ML techniques can be used
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for improving airfields, communication systems, ammunition storage facilities, and other locations. In addition, you will learn about web visualization efforts that impact the design and construction mission
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to constrain the representation of aerosols in the NASA GEOS Earth System Model. Activities that would be involved in this project include (but are not limited to): Implement machine learning transfer learning
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on-site in Oak Ridge, Tennessee. $500 per week stipend based on full-time of participation each week. The opportunity to learn from world-renowned scientists and engineers. Optional professional development
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This research involves conducting fundamental and applied research in the field of Robotics and Autonomous Systems (RAS) and Artificial Intelligence/Machine Learning (AI/ML). The fellowship position is based
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aided design (CAD), computer aided manufacturing (CAM), manipulation of digital manufacturing software tools, 3D object slicers, support structure optimizers, computer programmings, and scripting
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improve federal transit operations and oversight. Projects may include: Performing exploratory data analysis across diverse FTA datasets. Building and evaluating statistical and machine learning models