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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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material property database for composites. The candidate will utilize the database to develop AI models for composite discovery. The candidate will work with a multidisciplinary team to set up finite element
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-principles and atomistic simulations with machine-learned interatomic potentials to: Model reaction pathways on metal-oxide surface, including adsorption, reactions and diffusion steps. Construct atomistic
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on developing a new hybrid light–matter platform that couples transition metal complexes with optical microcavities to achieve optical control over ultrafast spin conversion and charge transfer
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, materials science, or a related discipline Background and/or interest in one or more of the following areas: critical elements and materials, electrical double layer theory and applications, solid–liquid
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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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for molecular design (e.g., DFT, MD, AI/ML) is desired, but not required. · Strong oral and written communication skills are required. · Ph.D. in an experimental discipline, such as chemistry, materials
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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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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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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