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for candidates interested in the intersection of complex oxide epitaxy, quantum information, and nanophotonic to contribute to high-impact science at a national user facility. Key Responsibilities Develop and
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computational science expertise. The ALCF has an opening for a postdoctoral position in data management targeting AI applications at scale. The successful candidate will join the AL/ML group, a vibrant
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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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for a predoctoral/postdoctoral researcher position in research data management. Position Overview The candidate will manage and coordinate data activities across ESRA. You will work closely with
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computational science expertise. The ALCF has an opening for a postdoctoral position in data management targeting AI applications at scale. This Postdoc will join the AL/ML group, a vibrant multidisciplinary team
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The Center for Nanoscale Materials (CNM) at Argonne National Laboratory seeks an outstanding postdoctoral researcher to advance data-driven, physics-informed AI for microelectronics materials
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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. The candidate is expected to lead an effort to prepare generalized ML techniques for data quality monitoring for tasks across multiple HEP experiments. Experiments with Argonne involvement include, but are not
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techniques to solve pressing challenges in energy storage. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne
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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