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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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modeling tools to develop and optimize new processes and equipment designs using high-performance computing Analyze data, prepare manuscripts for submission to peer-reviewed publications, prepare technical
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is supported by a DOE-funded research program on ultrafast science involving Argonne National Laboratory, University of Washington, and MIT. The goal of this research program is to understand and
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focus on our scientific program with CLAS12 (including the ALERT), Hall C and PRad-II at Jefferson Lab, and/or development of the EIC scientific program, including the development of a polarized light ion
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, computational physics and x-ray science. The appointee will benefit from access to world-leading experimental and computational resources at Argonne including some of the world’s largest supercomputers (Polaris
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reduction approaches and systems will be developed and implemented that operate close to instruments at the edge, and that leverage high-performance computing environments when needed. This position will be
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, in Electrical Engineering and Computer Science or related field obtained within the last five years. Experience with X-ray physics or optical wave modeling. Proficiency in programming with Python
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in spatial analysis and data visualization Computer programming skills relevant for data manipulation and analysis Experience with creating and using complex data-driven analytical models using R
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Electrical Engineering, Computer Science, Operations Research, or a closely related field. Experience in power systems, distribution systems, or microgrid modeling, with a solid understanding of advanced co
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-inspired research relevant to microelectronics. The candidate will be part of a highly interdisciplinary project involving X-ray scientists, physicists, materials scientists, and computational scientists