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. Perform research on power system dynamics and control under high inverter-based resources (IBRs). Develop and apply artificial intelligence (AI)/machine learning (ML) techniques for power system planning
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finishing high-curvature X-ray mirrors. o Enhance the determinism (predictability) of the IBF process by leveraging artificial intelligence or machine learning (AI/ML). • Publish results in peer-reviewed
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electron microscopy (TEM). In this position, you will be a member of the Electron Microscopy group and closely collaborate with the Computational group. You will learn and develop advanced machine-learning
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spectroscopy, neutron scattering, etc. Familiarity with, or motivation to learn, facility proposal submission procedures and effective completion of experiments in fixed time slots using national-scale central
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signal processing and analysis Experience in applying machine learning to scientific problems Experience in heterogeneous computing (e.g. GPUs) OTHER INFORMATION: Please submit your resume/CV, research
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to apply for a postdoctoral research associate position in applied mathematics, scientific computing, and machine learning. This position offers a unique opportunity to conduct research in emerging
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to apply for a postdoctoral research associate position in applied mathematics, scientific computing, and machine learning. This position offers a unique opportunity to conduct research in emerging
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distribution. The candidate is expected to incorporate the latest machine-learning methods for increasing measurement and analysis throughput. In order to achieve this goal, the candidate is expected
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of the Electron Microscopy group and closely collaborate with the Computational group. You will learn and develop advanced machine-learning algorithms for TEM image analysis with guidance from
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) Machine Learning aided multimodal data analysis and reaction mechanism determination. You will contribute to the synthesis of thin-film and nanoparticle electrocatalyst libraries in collaboration with other