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monitoring and control technologies applicable to molten salt and liquid metal systems Develop and test new materials and cell configurations for the production of salt and metal products. Perform experiments
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key element of the two-beam acceleration concept Emphasize Bayesian optimization approaches and integrate these methods into the facility control system Design, execute, and analyze accelerator
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well as university partners on coastal methods and validation strategies. Mentor summer students on data analysis and visualization workflows. Publish in peer-reviewed journals, present at scientific conferences, and
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applying machine learning or other elements of artificial intelligence to solving significant scientific or engineering problems Interest in software development, with particular emphasis on the Python
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The High Energy Physics (HEP) Division at Argonne National Laboratory invites applications for a Postdoctoral Research Associate to join the ANL ATLAS group with a focus on physics analysis and
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total X-ray scattering (TXS) and pair distribution function (PDF) analysis capabilities and methodology to study laser-driven structural dynamics in functional materials. This position is part of a
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readout and controls (e.g., SQUID-based time- or microwave-multiplexed systems) with beamline data acquisition and control (EPICS/Bluesky). Develop and maintain data acquisition, calibration, and analysis
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, distributions, and dynamics in metallic, oxide, and semiconducting systems. This project integrates high-throughput and in situ TEM experimentation with AI/ML-driven image analysis and computational modeling
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, MATLAB, or similar programming environments for instrument control and data analysis. Excellent written and oral communication skills. Demonstrated ability to work both independently and collaboratively in
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experiments and corresponding data analysis. Following the successful demonstration of the technique, the candidate will collaborate with team members from material science to apply these methods to scientific