49 image-processing-and-machine-learning-"RMIT-University" Postdoctoral positions at Argonne
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, especially XAS and other X-ray spectroscopy techniques, nuclear magnetic resonance spectroscopy, infrared and ultraviolet spectroscopy, as well as experience with high resolution STEM imaging Excellent written
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resonance spectroscopy, infrared and ultraviolet spectroscopy, as well as experience with high resolution STEM imaging Excellent written and oral communication skills Requirements: Recent or soon-to-be
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using software, such as LAMMPS, and machine-learned potentials Experience in GPU programming with Kokkos An understanding of computer architecture and experience in the analysis and improvement
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experiments. Develop reinforcement learning models to improve gate fidelity. Leverage CNM’s state-of-the-art facilities, including the nanofabrication cleanroom and the Quantum Matter and Device Lab’s dilution
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source for EIC and the design of the ePIC Barrel Imaging Calorimeter. Argonne National Laboratory, situated near Chicago, is a prominent multidisciplinary science and engineering research center. We are
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multidisciplinary team comprised of fellow postdoctoral appointees, experimentalists, and staff scientists, with computational fluid dynamics (CFD) and artificial intelligence/machine learning (AI/ML) expertise, with
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experts across system software, power management infrastructure, performance characterization, networking, and novel computer architectures and accelerators. It will also involve collaboration with leading
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. Develop advanced optimization, control, or machine learning strategies for distribution systems; validate these strategies using hardware-in-the-loop or real-time grid simulators. Develop optimization
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The Chemical and Fuel Cycle Technologies division at Argonne is seeking a Postdoctoral Appointee to join a multidisciplinary team developing molten salt-based chemical and electrochemical processes
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data-intensive operations in scientific and AI applications. Investigate machine learning techniques to inform heuristic methods for routing optimization, bridging theoretical insights with practical