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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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materials recovery,CO2 electrolysis and fuel cells. Experimental work will involve design, characterization, and degradation studies of model interfaces that can help elucidate their degradation mechanisms
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in experimental physics and superconducting device development, with a focus on advancing multipixel single-photon camera technology and multiplexed readout for quantum information science applications
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, engineering, computational science, a physical science (materials science, chemistry, physics etc.), or related field. Hands-on experience with AI frameworks and employing large language models. Strong Python
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or soon-to-be-completed PhD (typically completed within the last 0-5 years) in chemistry, chemical engineering or materials science (those with other degrees but have similar skills to those listed will be
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relationships in next-generation electronic materials. This role involves creating AI models for real-time data analysis, enabling autonomous experiments through active learning and "curiosity-driven" exploration
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modeling and techno-economic assessment as appropriate. The candidate will work independently under general guidance, collaborate effectively within a multidisciplinary team environment, and prepare
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-based experiments, including accelerating gradient tests and breakdown studies of accelerating components. Collaborate with the APS/ASD mechanical engineering group on the fabrication of accelerator
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/modelers, and data scientists Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of Materials Science, Chemical Engineering, Chemistry, or a closely related field
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will be working with ALCF’s technical teams (e.g., AI/ML, Data Science, Performance Engineering) and will focus on collaborative APEX research projects. We are looking to hire four Postdoctoral