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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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-completed PhD (typically completed within the last 0-5 years) in chemical engineering, environmental engineering, or similar degree. Experience with data collection, processing, analysis, and presentation
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will require working on-site in Lemont, Illinois, 5 days a week Position Requirements Required skills, knowledge and experience: A recent or soon to be completed PhD within the last 0-5 years Molecular
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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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-field survey datasets. This position offers the opportunity to collaborate extensively with CPAC colleagues and the broader SPHEREx science team. Collaborative Environment and Resources The cosmology
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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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Applications are invited for post-doctoral positions in the Cosmological Physics and Advanced Computing Group (CPAC) Group in Argonne National Laboratory’s High Energy Physics (HEP) Division
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Laboratory’s Biosciences Division, allowing for seamless computational and experimental research integration Position Requirements A recent or soon to be completed PhD within the last 0-5 years Computational
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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