82 structural-engineering "https:" "https:" "https:" "https:" "https:" "https:" "Multiple" Postdoctoral positions at Argonne in United States
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The Data Science and Learning Division (DSL) of the Computing, Environment and Life Sciences Directorate (CELS) and the Materials Science Division (MSD) of the Physical Sciences and Engineering
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apply funding from federal agencies (e.g., the Department of Energy and National Science Foundation). A successful candidate should have a solid background in power system engineering, optimization
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, you will: Apply engineering principles to develop molten salt synthesis and separations processes to support fuel cycle science and technology. Develop and test new electrodes for use in molten salt
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, the postdoc will translate demonstrated prototype performance into a complete, buildable engineering specifications package for a scaled multi-element analyzer spectrometer and associated microscope/imaging
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Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of Chemistry, Chemical Engineering, Mechanical Engineering, Materials Science, Electrochemistry, or a related
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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
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Argonne National Laboratory invites applications for a postdoctoral research position in experimental physics, with a focus on advancing superconducting particle detector technology for next
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) simulations and reduced order modeling of turbulent and reacting flows relevant to advanced propulsion and power generation systems, such as gas turbines and detonation engines. The successful candidate’s
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, asphaltenes, resins, and kerogen molecules and contribute to engineering design of upscaled processes. The candidate will be a part of the Applied Materials Division (AMD) within AET at Argonne and will
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Science, Chemistry, Chemical Engineering, Electrical Engineering, Computer Science, Physics, or a related field Demonstrated proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow