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crop monitoring and decision-support systems for Controlled Environment Agriculture (CEA). This project focuses on the development, validation, and integration of non-destructive plant sensing
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crop monitoring and decision-support systems for Controlled Environment Agriculture (CEA). This project focuses on the development, validation, and integration of non-destructive plant sensing
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National Aeronautics and Space Administration (NASA) | Merritt Island, Florida | United States | about 7 hours ago
exploring how genomic selection approaches can identify plant cultivars with improved performance in space exploration environments. This research focuses on controlled-environment agriculture (CEA
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less). In the ANR/CEA-funded BrainSync collaborative project, we are interested in characterizing the neural representations of uncertainty6–8 and value that emerge from learning and guide decisions. Our
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Associate position focusing on control systems engineering, artificial intelligence (AI), and scientific machine learning (SciML) applied to nuclear fusion energy. The successful candidate will join the
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, experimental validation, and machine learning. A key feature of this position is the opportunity to collaborate with major U.S. and international fusion facilities (such as DIII-D, NSTX-U, KSTAR, WEST, and ITER
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Agriculture (CEA) Engineering Lab as a Postdoctoral Research Associate. The candidate will primarily work in one or more of the following areas: computer vision, AI-driven automation, and/or robotics