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simulations and experiments across scientific user facilities, leveraging data to understand complex material phenomena across scales. Key Responsibilities Design, implement, and validate physics-informed AI/ML
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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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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Requirements Required skills, abilities, and knowledge: Recent or soon-to-be completed PhD (within the last 0-5 years) by the start of the appointment in computer science, electrical engineering, applied
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. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical engineering, materials science, civil engineering, structural engineering, or a closely
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at the University of Chicago, automating screening protocols in partnership with Argonne National Laboratory Drive research at the intersection of automation, robotics, generative AI, and computational simulations
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-completed PhD with strong background in Materials Science or Physics (within the last 5 years) Considerable experience in understanding magnetic-domain physics in thin film and/or nanostructured materials
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architectures and device technologies Developing and applying simulation and modeling tools for detector performance, characterization, and validation Providing technical feedback to guide intelligent on-detector
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simulations. The candidate is expected to work as part of a collaborative team of chemists, physicists, and engineers to develop new chemistry for upgrading hydrocarbon streams. The candidate should be
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modeling of x-ray spectroscopies sensitive to molecular chirality; simulations of x-ray–induced ultrafast electron-transfer, decay, and nuclear dynamics in gas- and liquid-phase systems; and the development
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nonproliferation. With guidance, the appointee will : Develop advanced multiscale, multiphysics simulation tools relevant to the modeling of processes involving combined nuclear, chemical, and electrochemical