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computational science expertise. The ALCF has an opening for a postdoctoral position in data management targeting AI applications at scale. The successful candidate will join the AL/ML group, a vibrant
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growth, electricity usage, and their implications for U.S. supply chains and energy infrastructure plans. The successful candidate will apply methods from economics, supply chain risk analysis, and data
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team and contribute to IDEAS (Intelligent Data Exploration Assistant for Science), a multi-year research effort focused on developing AI-powered visualization systems that enable interactive, human-in
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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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materials from complex feedstocks to achieve the desired product quality and form. As a part of this team, you will: Apply electrochemical engineering principles to develop processes such as oxide reduction
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The Materials Science Division is seeking applicants for a Postdoctoral Appointee who will conduct cutting-edge research in AI for Materials Chemistry, with a focus on energy storage and conversion
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techniques to solve pressing challenges in energy storage. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne
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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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spectroscopy (e.g., transient absorption), including laser operation, optical alignment, and data analysis Experience in synthetic inorganic chemistry and transition metal complex photophysics Job Family
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optimization schemes. From developing AI models to uncover structure-function relationships with limited data sets, to building automated electrode-electrolyte interface discovery workflows and implementing full