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The Quantum Materials group at Argonne National Laboratory, in collaboration with the Argonne Quantum Foundry, a key component of Q-NEXT, seeks a highly motivated postdoctoral candidate to spearhead
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The High Energy Physics (HEP) Division, in collaboration with the Materials Science Division (MSD) and Q-NEXT at Argonne National Laboratory, seeks a postdoctoral researcher to focus on applied
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. The candidate will work closely with computational modeling collaborators to validate reactor designs and optimize operating parameters. The candidate will be expected to contribute to report preparation
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learning, or optimization Strong programming skills in Python and experience with scientific computing and machine-learning libraries Ability to work across experimental, robotic, and computational systems
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Argonne National Laboratory in the Nanocomposite Materials and Membrane Manufacturing Group within the Applied Materials Division (AMD) seeks a highly motivated Postdoctoral Appointee to conduct
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computational models for industrial capacity planning, logistics optimization, material flow analysis, and supply chain analysis. Apply artificial intelligence, machine learning, LLMs, and advanced statistical
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that span computation, data science, and experiment Application Materials Updated CV/Resume Unofficial Ph.D. transcripts If already awarded, a copy of the Ph.D. diploma Job Family Postdoctoral Job Profile
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The Materials Science Division at Argonne National Laboratory invites applications for a postdoctoral appointment focusing on the project of axion dark matter detection with magnon quantum sensing
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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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pressure-temperature measurements with advanced x-ray platforms. This includes working in optimizing applicaton of APS-Upgraded high brightness and high coherence beam across APS and at HPCAT and