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regard to any characteristic protected by law. Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
mathematics, or a related field Candidates should have expertise in two or more of the following areas: Uncertainty quantification, numerical solutions of differential equations, and stochastic processes
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) or equivalent experience in a computational science discipline, computer science, or in a related field Strong programming skills in one or more scientific programming language, such as C++ and Python Experience
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a broad spectrum of research activities, utilizing state-of-the-art instrumentation at beamline 32-ID. The use of holotomography with PXM enables full-field imaging with spatial resolutions ranging
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encouraged to apply. The selected individual will have access to state-of-the-art research facilities and gain in-depth knowledge of the research frontiers in the fields of quantum materials. He/she will also
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equipped with world-leading full-field imaging instruments, including ultrahigh-speed imaging. The group also develops end-to-end scientific software, data analysis, and interpretation methods
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should have a strong background in experimental physics and/or engineering, or in a relevant field. Experience in superconducting qubits, nanofabrication, photonics, and low-temperature experiments
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policy, environmental science, or a related field at the PhD level with zero to five years of employment experience. Technical background in economics with a focus on the mineral and energy sectors. Proven
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basic and applied research in the field of metallization and metal production, such as molten salt electrolysis, metallothermic reduction, including physico-chemical property determination. The candidate
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relevant field at the PhD level with zero to five years of employment experience. Experience with deep learning frameworks (PyTorch, TensorFlow, JAX). Strong background in computational image processing and