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behavior, materials, neutronics, thermal-hydraulics, and structural mechanics. The candidate will assist in investigation of the performance of nuclear fission reactors and fuel cycle facilities and
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research encompasses fundamental chemistry of the f-elements, synthesis, structure and spectroscopy, along with collaborative efforts in developing fundamental descriptions of chemical separations including
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generalized ML techniques for data quality (DQ) monitoring/assurance for tasks across multiple HEP experiments. Among the experiments with Argonne involvement are ATLAS at CERN, DUNE, g-2, Mu2e, LSST-DESC, LZ
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interfaces, or Langmuir trough techniques Experience with structural investigation of liquid interfaces, or ion adsorption at liquid interfaces A basic understanding of chemical separations of metal ions Job
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structure, nuclear astrophysics, fundamental symmetries, and nuclear data. The Group also manages and operates world-class detector systems as part of the ATLAS accelerator facility, a DOE Office of Nuclear
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the synthesis and characterization of the structural, electronic, and/or magnetic properties of inorganic quantum materials, including air-sensitive compounds. (PhD must have been received within the last 3 years
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nanomaterial synthesis and crystal structure analysis using XRD Rietveld analysis Knowledge of solid-state materials synthesis and use of structure construction software such as Materials Studio, Crystalmaker
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rotating disk electrode and H-cell, as well as full-cell electrolyzers Perform catalyst structural characterization using conventional analyses such as XRD, BET, XFS, SEM, TEM, as well as the advanced
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reactivity in sustainable energy conversions. Perform theoretical calculations of the electronic structure and chemical kinetic modeling for combustion/atmospheric/sustainable-energy-conversion chemistry
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for such models include high-resolution 3D imaging, time-resolved materials characterization, and atomic structure determination. Scientific instrument data is often multimodal in nature and developing DL models