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The High Energy Physics Division at Argonne National Laboratory invites applications for a postdoctoral research associate position to conduct research in machine learning (ML) for applications in
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. Cosmological research within CPAC covers theory, modeling, observations, and experiments targeted at dark energy, dark matter, primordial fluctuations, inflation, and neutrinos. Theory and modeling activities
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University of Chicago Comprehensive Cancer Center, the postdoctoral researcher will work closely with a multidisciplinary team of computational and experimental biologists. The team is dedicated to developing
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The Microscopy group in X-ray Science Division of Advanced Photon Source at Argonne National Laboratory is seeking postdoctoral researchers to work on cutting-edge ptychography technique development
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for Microelectronics” —a physics-informed AI framework that links composition, structure, and operating conditions to defect evolution and functional performance. The successful candidates will lead experimental
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material property database for composites. The candidate will utilize the database to develop AI models for composite discovery. The candidate will work with a multidisciplinary team to set up finite element
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work with a collaborative, interdisciplinary team with expertise in materials synthesis, characterization, and theoretical understanding to design and optimize functionalized electrodes for next
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spectrometers at the Advanced Photon Source. The successful candidate will work at the interface of cutting-edge cryogenic detector technology and synchrotron science, helping to integrate TES spectrometers
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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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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced