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We are seeking a Postdoctoral Appointee - Data Management Techniques for AI/Machine Learning. A candidate with expertise at the intersection of HPC and AI. Major efforts at Argonne in this direction
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position to develop and apply advanced analysis methods, including artificial intelligence and machine learning algorithms and approaches, for x-ray science and instruments. These methods will accelerate
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The High Energy Physics Division (HEPD) at Argonne National Laboratory invites applications for a postdoctoral research associate position to conduct research in machine learning (ML
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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 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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staff scientists with computational fluid dynamics (CFD) and artificial intelligence/machine learning (AI/ML) expertise, with the goal to enhance predictive capability and scalability of multi-scale and
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and applying algorithms and software for the use of first principles and atomistic modeling, together with machine learning, to accelerate the inversion of experimental characterization data
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(MERF), the Nanocomposite Materials and Membrane Manufacturing group perform science-based membrane synthesis and scaleup development by using roll-to-roll manufacturing and machine learning enabled in