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in modeling, analysis and control of electric power distribution and transmission system, applying state of the art machine learning (ML) and deep learning algorithms to develop cybersecurity
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Argonne National Laboratory, a U.S. Department of Energy National Laboratory, has an opening for a Postdoctoral Appointee specialized in physics-informed machine learning at the Department
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for machine learning/AI model development development using Pytorch, Tesnor Flow or similar platforms. Utilization of high-performance computational platforms. Writing and modifying scientific code in Fortran/C
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of the art machine learning and deep learning algorithms to develop cybersecurity, optimization, and control solutions for transmission and distribution system operators. Job duties but not limited to: Develop
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The X-ray Imaging group (IMG) of the Advanced Photon Source (APS) is currently seeking a postdoc with expertise in machine learning (ML) and image processing to develop cutting edge processing
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of machine learning in electronic structure calculations and advanced sampling. The postdoctoral researcher will work within the groups of Professor Giulia Galli (https://galligroup.uchicago.edu/ ) and Dr
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position to develop and apply machine learning algorithms and approaches for x-ray science and instruments. These machine learning methods will be integrated into a shared platform that will lower
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Appointee position planned to start around March-April, 2024. The successful candidate will be primarily working with physicists and computer scientists in the development of an automated machine-learning (ML
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, respect, integrity and teamwork. Desired skills and qualifications: Experience with automatic differentiation and generation of derivatives. Experience with machine learning methods. Job Family Postdoctoral
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multidisciplinary team comprised of fellow postdoctoral appointees and staff scientists with computational fluid dynamics (CFD) and artificial intelligence/machine learning (AI/ML) expertise, with the goal to enhance