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through the design and synthesis of nanoscale epitaxial oxide thin films. This position supports a three-year Laboratory Directed Research and Development (LDRD) project focused on developing scalable
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The Time-Resolved Research Group in the X-ray Science Division at Argonne National Laboratory invites applications for a Postdoctoral Appointee. The role focuses on developing ultrafast pump–probe
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advanced synchrotron X-ray techniques. The successful candidate will be at the forefront of integrating cutting-edge AI methodologies with world-leading X-ray characterization. You will develop and apply
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programming, interfacing hardware, and developing machine-learning methods highly desirable. The researcher will join an Argonne funded project with interdisciplinary team of material scientists, computer
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to develop and lead a world-class research program that strongly aligns with DOE priorities in low energy nuclear physics, as outlined in the 2023 Nuclear Science Advisory Committee Long Range Plan for Nuclear
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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
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reaction pathways that have potential impact on aqueous pollution remediation. Deeper insights into water-solid interfaces are essential for development of innovative and efficient technologies to extract
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photonic platforms through nano- and meso-scale lithographic fabrication. This position supports two complementary, three-year Laboratory Directed Research and Development (LDRD) projects focused on hybrid
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We are seeking a highly motivated and flexible postdoctoral researcher to join the Applied Materials Division (AMD) at Argonne National Laboratory to develop advanced methods for in situ and
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multidisciplinary team of scientists and High Performance Computing (HPC) engineers. In the AL/ML group, we work at the forefront of HPC to push scientific boundaries, carrying out research and development in state