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collaborators, and other national laboratories, the successful candidate will develop and apply transparent, parameterized models of mineral extraction, concentration, refining, chemical conversion, battery
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innovative approaches to enhance predictive skill. The role also involves integrating AI/ML techniques to advance physical parameterizations and improve severe weather prediction skills. Key responsibilities
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-be-completed PhD (typically completed within the last 0-5 years) in chemistry, chemical engineering, materials science or related field. Knowledge and hands-on experience in the following areas
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), in collaboration with Argonne researchers and external partners from industry and academia. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in
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help shape technologies with broad relevance to future quantum systems. Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of physics, electrical engineering
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. Position Requirements A formal education in materials science and engineering, nuclear engineering, or a related field at the PhD level with zero to five years of employment experience. Knowledge of metallic
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requires hands-on laboratory work to develop and synthesize and analyze new organic materials, specifically new battery electrolyte materials. Position Requirements Recent or soon-to-be-completed PhD
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. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in chemistry, materials science, metallurgy, electrochemistry, electrometallurgy, chemical
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for accelerator operation. Position Requirements PhD completed in the past 5 years or soon-to-be completed in accelerator physics or a related field is strongly preferred. PhD graduates in other branches
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to contribute to both the scientific and technical aspects of the ATLAS program in a highly collaborative research environment. Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years