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for predicting the reliability of high-temperature structural components. This involves working with various continuum damage mechanics models and statistical reliability models. The goal is to enhance 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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projects in artificial intelligence, materials engineering, chemistry, and beyond at Argonne National Laboratory. Position Requirements Recently completed PhD within the last 0-5 years in computer science
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engineering controls such as gloveboxes or hoods is desired, but not mandatory. Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork. Other: To perform the essential
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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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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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and supercritical conditions. The ability to assemble new batch and flow processes is a plus. Furthermore, we will teach the candidate about engineering design of chemical processes; however
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national laboratories. The successful candidate will support technical and economic analyses of power systems with a particular focus on hydropower systems. The successful candidate will develop and apply
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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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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