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The Argonne Leadership Computing Facility (ALCF) is dedicated to advancing scientific discoveries and engineering breakthroughs by providing world-class computing facilities in collaboration with
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(predoctoral) or PhD (postdoctoral) in Materials Science, Chemistry, Physics, or related area is required. Coursework in computer science or data science is desirable. Familiarity with research data management
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within the last 0-5 years) in computational science, mathematics, physics, or a related field with a focus on image processing. Proven experience in algorithm and software development. Expertise in Python
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device operation. The project involves large-scale simulations on exascale computing resources to probe switching behavior while accounting for effects of defects, competing metastable phases, doping
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, synthesize, and process information to develop high-quality datasets and derive empirically driven results; work with other team members to develop and apply cutting-edge methodologies to address critical
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Electrical Engineering, Computer Science, Operations Research, or a closely related field. Experience in power systems, distribution systems, or microgrid modeling, with a solid understanding of advanced co
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fundamental understanding of reaction mechanisms in molten salts and apply insights to process development and scale up. Project activities will include the design and development of online monitoring tools
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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electrolyzer materials and electrodes using synchrotron X-ray techniques at Argonne’s Advanced Photon Source (APS). In particular X-ray absorption spectroscopy, X-ray scattering, and nano-computed tomography
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The Computational Science Division (CPS) at Argonne National Laboratory (near Chicago, USA) is seeking a postdoctoral researcher to enable exascale atomistic simulations of ferroelectric devices