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inverter-based resources for performing real-time simulations in Opal-RT. Develop and prototype advanced control algorithms for grid forming and grid following inverters. Develop and demonstrate
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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within the last 0-5 years) in computational science, mathematics, physics, or a related field with a focus on image processing. Proven experience in algorithm and software development. Expertise in Python
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encompass: Catalysts Synthesis: Utilize your expertise in materials synthesis to develop novel catalysts guided by machine learning algorithms Catalyst Performance Evaluation: Utilize aqueous electrochemical
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The Nuclear Science and Engineering (NSE) Division is seeking a postdoctoral appointee to develop computational methods and computer codes to model the physics and engineering of advanced nuclear
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position to develop and apply advanced analysis methods, including artificial intelligence and machine learning algorithms and approaches, for x-ray science and instruments. These methods will accelerate
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The Chemical and Fuel Cycle Technologies division at Argonne is seeking a Postdoctoral Appointee to join a multidisciplinary team developing molten salt-based chemical and electrochemical processes
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The Applied Materials Division (AMD) at Argonne National Laboratory is seeking a Postdoctoral Appointee to contribute to the research, development, and manufacturing of advanced cathode materials
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candidate will work on cutting-edge research integrating genome-scale language models (GenSLMs) with deep mutational scanning data, and experimental virology to predict viral evolution and identify emerging
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The Postdoctoral Appointee will be part of an R&D group conducting use-inspired research supporting the development of process technologies for next-generation nuclear/chemical/electrochemical