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advanced computing, optimization, and data analytics technologies. The postdoctoral researcher will work with a team of researchers on solving challenging problems using optimization, stochastic models
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The successful candidate will be highly motivated and have a strong track record in problem solving and scientific publications. The candidate will be expected to conceive of, plan, and implement scientific
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information science and light–matter engineering, while engaging with CNM’s cleanroom and characterization capabilities, APS ultrafast and nanoprobe X-ray beamlines, MSD’s THz initiatives, and Q-NEXT’s national quantum
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electrocatalyst materials Plan and execute in situ/operando studies using advanced techniques such as X-ray Absorption Spectroscopy (XAS), X-ray Photoelectron Spectroscopy (XPS), Raman spectroscopy, Differential
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experience in economic and supply chain analysis, computational modeling, or policy analysis. Proficiency in scientific programming languages (e.g., Python, R) and data analysis libraries (e.g., pandas, NumPy
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scientists with extensive microelectronics (materials and devices), AI, computational materials science and materials characterization expertise; and will be expected to bring the electrochemical expertise
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engineering principles Experience working safely with hazardous materials using engineering controls such as gloveboxes is desired. Knowledge of the use of computers to design and control experiments and to
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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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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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phenomena Create new reduced-order models and submodels related to fluid flow, heat transfer, thermochemistry, and electrochemistry in multiphase systems Use modeling tools such as computational fluid