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, high-efficiency transmitters, low-phase noise RF sources, and other critical radar components. Topics also cover radar signal processing and machine learning, applying advanced techniques to enhance
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? Under the guidance of a mentor, you will engage in activities and research that will expanding your learning in several areas. These include, but are not limited to: Fabricating new plasmonic (gold
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missions (e.g., Surface Biology and Geology - SBG). This could involve advancing atmospheric correction, dimensionality reduction, or machine learning approaches for handling big data in order to improve
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to: Learning about aircraft systems engineering and systems analysis to support integrated design and performance assessment. Participating in aircraft design trade studies with a focus on propulsion–airframe
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continued development. Learning Objectives: You will gain a rich, hands-on professional development experience grounded in real-world application of artificial intelligence, workflow analysis, and federal
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related area, including meteorology, hydrometeorology, remote sensing, surface and atmospheric modeling, or related fields. Experience in machine learning techniques are highly desirable. Please see https
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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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, fostering the research necessary to maintain global competitiveness in innovative technologies. The learning objectives for this project are: • Developing innovative approaches that effectively convert REE/CM