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and emissions associated with energy systems, including sustainability of various energy products, services and chemicals. Position Requirements PhD degree in chemical engineering, mechanical
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and emissions associated with energy systems, including sustainability of various energy products, services and chemicals. Position Requirements PhD degree in chemical engineering, mechanical
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staff scientists with computational fluid dynamics (CFD) and artificial intelligence/machine learning (AI/ML) expertise, with the goal to enhance predictive capability and scalability of multi-scale and
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: This level of knowledge is typically achieved through a formal education in nuclear engineering or energy science, or a related field at the PhD level with zero to five years of employment experience
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Completed or soon-to-be completed PhD (within the last 0-5 years) in Computer Science, Physics, Mathematics, or related field Experience with modeling complex systems or natural language processing
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(MERF), the Nanocomposite Materials and Membrane Manufacturing group perform science-based membrane synthesis and scaleup development by using roll-to-roll manufacturing and machine learning enabled in
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measurements, searches for new physics, Higgs measurements, and performance studies. The Argonne group also has significant involvement in detector operations, TDAQ upgrades, Software and Computing, Machine
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techniques, and will also be instrumental in developing sophisticated data analysis software that incorporates machine learning and artificial intelligence. The successful candidate must be able to work onsite
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apparatus to solve challenges. The position will require flexibility and a willingness to learn new techniques and approaches. The postdoctoral appointee will have the opportunity to work on projects
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the national and international levels. The appointment can be extended up to three years and is based at Argonne. Position Requirements The candidates must have received a PhD degree in electrical engineering