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, synthesize, and characterize metal-organic frameworks (MOFs) for catalytic applications Evaluate catalytic activity for hydrocarbon conversion and hydrogen (H2) storage in liquid organic hydrogen carriers
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engine modeling code. Perform high-fidelity CFD simulations of turbulent and reacting flows pertaining to gas turbines and detonation engines using spectral element method (SEM). Perform scalability
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key element of the two-beam acceleration concept Emphasize Bayesian optimization approaches and integrate these methods into the facility control system Design, execute, and analyze accelerator
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monitoring and control technologies applicable to molten salt and liquid metal systems Develop and test new materials and cell configurations for the production of salt and metal products. Perform experiments
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programming, interfacing hardware, and developing machine-learning methods highly desirable. The researcher will join an Argonne funded project with interdisciplinary team of material scientists, computer
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collaborative effort across XSD, the Materials Science Division (MSD), and the Chemical Sciences and Engineering Division (CSE). Key Responsibilities: Develop and enhance pump–probe sub-nanosecond TXS method
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for new physics and performance studies. Candidates with experience in modern AI/ML methods—such as transformer architectures, tokenization strategies, and embeddings—are especially encouraged to apply
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of molten salt chemistry and electrochemistry Develop novel process monitoring and control technologies applicable to molten salt and liquid metal systems Develop advanced molten salt flow systems to enable
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surface organometallic catalysis with a focus on understanding metal-surface stereoelectronic communication. In this role you will: Conduct research as part of a multidisciplinary team in supported
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field Match at least one of the following profiles: Experience with modern AI methods for nuclear physics or high-energy physics detector data; or Hands-on work with PMTs, SiPMs, or MCP-PMTs (test-beam