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dynamics. This position focuses on advancing fundamental understanding of light-matter interactions with direct relevance to energy conversion. The research involves exploring the excited-state dynamics and
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The Data Science and Learning Division (DSL) at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting edge molecular and microbiology work to enhance non-proliferation
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for dynamics imaging. The primary goal of this project is to develop single-frame ptychography methods that eliminate the need for scanning, enabling fast imaging and the visualization of dynamic processes in
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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The High Energy Physics Division at Argonne National Laboratory invites applications for a postdoctoral appointment focused on the design and simulation of advanced detectors for future high-energy
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specifically on developing machine learning-based surrogates and emulators for the dynamics of power grids. This role involves creating advanced probabilistic models that capture the complex behaviors
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The Multiphysics Computations Section at Argonne National Laboratory is seeking to hire a postdoctoral appointee for performing high-fidelity scale-resolving computational fluid dynamics (CFD
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for holotomography and to perform dynamic experiments using the Projection X-ray Microscope (PXM) instrument for studying microelectronics. As part of a collaborative team, the successful candidate will participate in
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structural models and compute electronic and vibrational properties. Develop and train neural-network or other machine-learned interatomic potentials to enable large-scale molecular dynamics (MD) simulations
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application of ultrafast THz-pump and optical-probe techniques to detect narrow-band THz radiation and explore mode-selective dynamics in quantum and molecular systems. This work leverages state-of-the-art