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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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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
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effort at Argonne includes staff members from CPAC, the Computational Science division, and the HEP Detector group. It includes a vibrant community of postdoctoral researchers, graduate students, and
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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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The Data Science Learning Division at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting-edge computational and systems biology research. The primary focus
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. The cosmology effort at Argonne includes staff members from the CPAC group, the Computational Science division, and the HEP Detector Group. The group also includes many postdocs, and a number of graduate and
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PhD (within the last 0-5 years) in field of physics, chemistry, materials science, electrical engineering, or a related field Demonstrated expertise in electronic structure theory Experience with large
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at technical conferences. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical engineering, materials science, civil engineering, computer science
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The Microscopy group in X-ray Science Division of Advanced Photon Source at Argonne National Laboratory is seeking postdoctoral researchers to work on cutting-edge ptychography technique development
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models Disseminate research through publications, presentations, and open-source contribution Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Data