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-aware multi-modal deep learning (DL) methods. At Argonne, we are developing physics-aware DL models for scientific data analysis, autonomous experiments and instrument tuning. By incorporating prior
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defect centers. This project aims to explore the use in-situ x-ray diffraction techniques available at the newly-upgraded Advanced Photon Source synchrotron at Argonne as a means to gain new insights
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. The second aim of the project will use the digital twin to develop experimental methods and algorithms to enable robust phase retrieval of reciprocal space measurements to direct space images. These methods
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a broad spectrum of research activities, utilizing state-of-the-art instrumentation at beamline 32-ID. The use of holotomography with PXM enables full-field imaging with spatial resolutions ranging
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-energy physics or detector technology. The positions are for up to three years and offer a highly competitive salary. The review of applications will start on February 1st. These positions will primarily
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equipped with world-leading full-field imaging instruments, including ultrahigh-speed imaging. The group also develops end-to-end scientific software, data analysis, and interpretation methods
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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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collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without
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Argonne National Laboratory, a U.S. Department of Energy multidisciplinary science and engineering research center, is committed to finding solutions for national priorities, including advancing
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We invite you to apply for a Postdoctoral Appointee position in the Chemical Sciences and Engineering Division (CSE) at Argonne National Laboratory. This position offers the opportunity