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camera technology and multiplexed readout systems for quantum information science applications. In this role, you will join a multidisciplinary team spanning several Argonne divisions and contribute
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The Chemical Sciences and Engineering Division invites applications for a Postdoctoral Appointee to contribute to innovative research at the intersection of computational catalysis, quantum
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ideal for someone who enjoys working at the intersection of data science, machine learning, materials research, and experiment, and who is motivated to translate computational advances into real
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The Data Science Learning Division at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting-edge computational and systems biology research. The primary focus
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bench scale micro-computed tomography and ultrasonic sensing methods to evaluate the state of charge and state of health of iron- and lead-based electrodes. Your research will be complemented by studies
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. The candidate will work closely with computational modeling collaborators to validate reactor designs and optimize operating parameters. The candidate will be expected to contribute to report preparation
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Position Overview We are seeking a Postdoctoral Appointee to join the Computational Science and Artificial Intelligence Group in the X-ray Science Division of the Advanced Photon Source (APS
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fluorescence tomography at beamline 2-ID-E and 2-ID-D with focus on bioimaging of soil aggregates, as well as computational framework for modeling and reconstruction of related 3D datasets. The successful
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implementing BCDI, XPCS, nano-beam and time resolved microscopy, PDF, 3D imaging techniques, PCI, and other techniques for advanced characterization of materials across solid-liquid and into melt. Measurements
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processes for energy storage applications. The researcher is expected to use solution-based synthesis approaches (e.g., electrospinning, slot-die coating, and 3D printing) to fabricate battery electrodes and