68 computer-programmer-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "U.S" Postdoctoral positions at Argonne
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Argonne National Laboratory, a U.S. Department of Energy multidisciplinary science and engineering research center, is committed to finding solutions for national priorities, including advancing
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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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in materials for electrochemistry. While the focus in on computational expertise, this position will involve some experimental work in adapting workflows for automation and artificial intelligence
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites outstanding candidates to apply for a postdoctoral position in the area of uncertainty quantification and
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. This position offers an exciting opportunity to contribute to fundamental and applied research in materials chemistry using advanced computational techniques and artificial intelligence. The project involves: 1
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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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Extensive knowledge of Microsoft Excel and good computer programming skills Knowledge of techno-economic analysis and life cycle analysis Experience working with Argonne’s EverBatt model, GREET model, and
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detectors while also having flexibility to pursue your own research interests. Research Focus Participate in a detector R&D program aimed at developing superconducting nanowire sensors to enable
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limited to, ATLAS at CERN, the South Pole Telescope, and the Simons Observatory. The candidate is also expected to work closely with computational experts at the Computational Science (CPS) division
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physics (HEP) and nuclear physics (NP) experiments. The successful candidate will be a key member of a multidisciplinary co-design team integrating materials science, computing, and device engineering to