54 computational-physics-"https:"-"https:"-"https:"-"https:" Postdoctoral positions at Argonne
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. The selected candidate will develop computational models at the mesoscale and/or macroscale based on the principles of mass, momentum, and energy conservation to describe processes such as morphological change
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platform for X-ray absorption spectroscopy by integrating LLMs, scientific machine learning, physics-aware workflows, and strong computational chemistry/electronic-structure expertise. The researcher will
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four staff members [Ian Cloët, Alessandro Lovato, Anna McCoy, and Yong Zhao] and several postdocs and students. The group has a broad research program in QCD/hadron physics and nuclear structure
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-completed Ph.D. within the last 0-5 years in Atmospheric Science, Meteorology, Climate Science, Applied Mathematics, Data Science, or a related field with strong quantitative and computational research
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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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The Environmental Science Division at Argonne National Laboratory seeks a highly motivated postdoctoral researcher to advance the understanding and prediction of severe weather using both physics
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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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, enabling multimodal in-situ investigation in areas of physics, chemistry, life and material sciences. We are seeking to fill a Postdoctoral Appointee position to support instrumentation development for X-ray
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from various scientific backgrounds (Physics, Chemistry, Materials Science, Geoscience, and Engineering, etc.) will be considered. Recent or soon-to-be completed PhD (within the last 0-5 years) in
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for Microelectronics” —a physics-informed AI framework that links composition, structure, and operating conditions to defect evolution and functional performance. The successful candidates will lead experimental