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electrochemical methods such as cyclic voltammetry and electrochemical impedance spectroscopy is desired, but not required. · Experience working directly or collaboratively with computational methodologies
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The Surface Scattering and Microdiffraction (SSM) group in the X-ray Science Division (XSD) at the Advanced Photon Source (APS), Argonne National Laboratory is seeking Two Postdoctoral Appointees, both focused on multimodal synchrotron characterization of defects and interfaces in oxides and 2D...
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, distributions, and dynamics in metallic, oxide, and semiconducting systems. This project integrates high-throughput and in situ TEM experimentation with AI/ML-driven image analysis and computational modeling
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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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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The Computational Science Division (CPS) at Argonne National Laboratory (near Chicago, USA) is seeking a postdoctoral researcher to enable exascale atomistic simulations of ferroelectric devices
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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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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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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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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