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. (typically completed within the last 0-5 years) in computer science, applied mathematics, operations research, engineering, economics, or a related quantitative field. Demonstrated expertise in AI, machine
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. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne National Laboratories. Primary responsibilities will be
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experiments. Experience: Ph.D degree in the field of Condensed Matter Physics, experimental High Energy Physics, Quantum Information Science, or a closely related discipline. Demonstrated experience in quantum
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is supported by a DOE-funded research program on ultrafast science involving Argonne National Laboratory, University of Washington, and MIT. The goal of this research program is to understand and
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in experimental physics and superconducting device development, with a focus on advancing multipixel single-photon camera technology and multiplexed readout for quantum information science applications
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The Microscopy group in X-ray Science Division of Advanced Photon Source (APS) at Argonne National Laboratory lead pioneering efforts in developing cutting edge X-ray instrumentation and techniques
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The Chemical Sciences and Engineering Division seeks a Postdoctoral Appointee to conduct research focused on the development of high-energy, long-cycle-life lithium–sulfur batteries employing both
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materials from complex feedstocks to achieve the desired product quality and form. As a part of this team, you will : Apply electrochemical engineering principles to develop processes such as oxide reduction
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have a strong background in fundamental electrochemistry, with preferable hands-on expertise in computational materials science. The applicant should be well versed in code development, application of AI
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The Applied Materials Division (AMD) at Argonne National Laboratory is seeking a Postdoctoral candidate in the area of organic chemistry with focus on battery electrolyte materials. This position