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Education and Experience Requirements : This level of knowledge is typically achieved through a formal education in Nuclear Engineering, Physics, or a related field at the PhD level with zero to five years
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inverter-based resources for performing real-time simulations in Opal-RT. Develop and prototype advanced control algorithms for grid forming and grid following inverters. Develop and demonstrate
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. This work involves developing novel techniques, algorithms, and software packages that enable more robust and scalable approaches to cybersecurity using AI-based techniques. In addition to technical
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into tangible products. Critically, this work will generate a large open-source dataset of child-created games that can inform future designs of educational games and AI algorithms. The postdoctoral fellow will
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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investigate AI/ML algorithms to deliver behavioral interventions at the moments of need and how those can/should be modified to account for personalized preferences. To accomplish this goal, we study behavior
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mathematical algorithm in codes and work on submitting papers Analyze theoretical and numerical results, summarizing findings in reports. Write and submit papers for publishing in peer-reviewed journals and
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the brain. We are particularly looking for a PhD level systems neuroscientist with expertise in animal behavior tracking using deep learning algorithms and its causal link with specific neural circuits
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that incorporate latest machine-learning algorithms). Furthermore, the successful candidate will collaborate broadly with the other members of IO and CFN, leveraging their expertise in design and fabrication
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Description NREL is seeking a postdoc to design, train, and analyze the AI/ML and control algorithms for hybrid energy systems including industrial systems, building controls, and advanced energy systems