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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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formal education in chemical engineering, chemistry, materials science, nuclear engineering, mechanical engineering, or related field at the PhD degree level with zero to five years of experience
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, instrumentation, modeling, and data science Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field(s) of materials science, physics, computational science, or a related field
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leaching, solvent extraction, ion exchange, electrodialysis, membrane separation, and crystallization or precipitation. Position Requirements Recent or soon-to-be-completed PhD (typically completed within
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, or a related field at the PhD level with zero to five years of employment experience. Technical background in economics with a focus on the mineral and energy sectors. Proven scholarly work or industry
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to the development of new research directions aligned with program goals. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in Chemical Engineering, Materials
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advanced computing, optimization, and data analytics technologies. The postdoctoral researcher will work with a team of researchers on solving challenging problems using optimization, stochastic models
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, materials synthesis, and separation processes. Position Requirements Recent or soon-to-be-completed PhD (typically within the last 0–5 years) in chemistry, geochemistry, chemical engineering, physics
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detectors while also having flexibility to pursue your own research interests. Research Focus Participate in a detector R&D program aimed at developing superconducting nanowire sensors to enable
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The Q-NEXT National Quantum Information Science and Research Center based at Argonne National Laboratory invites applications for a postdoctoral position to conduct research in the field