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data processing and interpretation workflows. The appointee will also pursue a collaborative science program leveraging the developing instrument capabilities, leading to peer-reviewed publications and
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in computational science, machine learning, and experience with synchrotron data analysis are strongly encouraged to apply. Position Requirements PhD completed in the past 5 years or soon to be
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field. Solid knowledge, and independent research capability in optimization, computing, power system engineering with track records of publications. Proficient in implementing control and optimization
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physics (HEP) and nuclear physics (NP) experiments. The successful candidate will be a key member of a multidisciplinary co-design team integrating materials science, computing, and device engineering to
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Argonne National Laboratory invites applications for a postdoctoral research position in experimental physics, with a focus on advancing superconducting particle detector technology for next
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(CFD) to develop and optimize new processes and equipment designs using high-performance computing Develop process- and facility-scale models as the foundation for digital twins of chemical processing
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3 years) in computer science, materials science, chemistry, physics, mathematics or related engineering disciplines Knowledge of deep learning techniques for time-series and image data Experience with
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the past five years or soon-to-be completed in physics, materials science, chemistry, engineering, or a related discipline. Demonstrated expertise in one or more synchrotron X-ray methods such as BCDI, XPCS
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information science and light–matter engineering, while engaging with CNM’s cleanroom and characterization capabilities, APS ultrafast and nanoprobe X-ray beamlines, MSD’s THz initiatives, and Q-NEXT’s national quantum
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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