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programming, interfacing hardware, and developing machine-learning methods highly desirable. The researcher will join an Argonne funded project with interdisciplinary team of material scientists, computer
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of molten salt chemistry and electrochemistry Develop novel process monitoring and control technologies applicable to molten salt and liquid metal systems Develop advanced molten salt flow systems to enable
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science, engineering, computational science, a physical science (materials science, chemistry, physics etc.), or related field. Hands-on experience with AI frameworks and employing large language models. Strong Python
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polymer chemistry is required. · Experience with molecular and/or surface characterization techniques (e.g., NMR, Raman, FTIR, electron microscopy, XPS) is required. · Experience with
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scientists with extensive microelectronics (materials and devices), AI, computational materials science and materials characterization expertise; and will be expected to bring the electrochemical expertise
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, the ALCF is studying the application of these techniques to a variety of our science applications, including but not limited to: Computational Chemistry, Plasma Physics, High Energy Physics, analysis
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chemistry, chemical engineering, physics, computational science, materials science, or related field. Background in synchrotron characterization techniques. Experience collecting and analyzing large
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of results at scientific conferences and in peer-reviewed literature. Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of interfacial chemistry, or materials
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of physical chemistry, inorganic chemistry, computational materials science, or chemical engineering or a closely related field, with demonstrated experience in the scientific application of this knowledge and
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or soon-to-be completed (typically within the last 0-5 years) in Materials Science, Chemical/Mechanical Engineering, Chemistry, Condensed Matter Physics, or a closely related field. Demonstrated experience