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The Center for Nanoscale Materials (CNM) at Argonne National Laboratory seeks a highly motivated postdoctoral researcher to join a multidisciplinary team advancing quantum information
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-throughput workflows for data acquisition and analysis Contribute to on-the-fly data processing and integration with computational tools Collaborate with multidisciplinary teams in nanofabrication
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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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lead efforts to develop experimental techniques using conventional and coherent imaging in the ultrafast time domain, as well as a computational framework for modeling and reconstructing images
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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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techniques in interfacial science; and mathematical techniques and computer programming for data analysis. Considerable skill in working interactively and productively in a multidisciplinary environment Good
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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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community In addition, the Group Leader is expected to develop and lead a world-class research program that strongly aligns with DOE priorities in low-energy nuclear physics, as articulated in the 2023
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engineering principles Experience working safely with hazardous materials using engineering controls such as gloveboxes is desired. Knowledge of the use of computers to design and control experiments and to
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experience in economic and supply chain analysis, computational modeling, or policy analysis. Proficiency in scientific programming languages (e.g., Python, R) and data analysis libraries (e.g., pandas, NumPy