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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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. Position Requirements A formal education in Physics, Materials Science, Chemistry, or a related field at the PhD level with zero to five years of employment experience. Demonstrated experience with high
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Requirements Required skills, abilities, and knowledge: Recent or soon-to-be completed PhD (within the last 0-5 years) by the start of the appointment in computer science, electrical engineering, applied
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; publish and present high-impact research results Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of materials science, physics, electrical engineering, or a
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We are seeking a highly motivated postdoctoral researcher to conduct independent research on foundation models for scientific and engineering applications, with an emphasis on training, adaptation
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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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Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of physics—ideally in accelerator science or engineering—or a closely related field Demonstrated experience or strong interest
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). About Argonne and the Physics Division: Argonne is a multidisciplinary science and engineering research center, where talented scientists and engineers work together to answer the biggest questions facing
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to contribute to other large-team scientific projects in materials engineering, chemistry, and beyond at Argonne National Laboratory. Position Requirements Required skills: Recently completed PhD (within the last
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scientists and engineers are accustomed to. Moreover, the vast majority of the performance associated with these reduced precision formats resides on special hardware units such as tensor cores on NVIDIA GPUs