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Duties/Responsibilities: Design and execute experimental investigations related to understanding process effects on chemical and physical observables of nuclear fuel cycle materials; improving
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improved process representations of nutrient (nitrogen and phosphorus) cycling and their coupling to hydrological and ecosystem processes within ELM and ELM-Peatlands. Evaluate model performance
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collaboratively support scientific advances guided by AI/ML, remote sensing, process-based modeling, field observations and experiments, and advanced analytical techniques. Major Duties/Responsibilities
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process design is preferred. Excellent written and oral communication skills. Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the
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-process scale-up; filtration, solvent or liquid-liquid extraction, solid-liquid or gas-liquid separation, membrane contactors, adsorption, or packed-column systems; extraction, separation, and
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expertise in multi-physics FE simulations is preferred. Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or process
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applications including thermo-mechanical response as well as microstructure and phase transformation response Demonstrated expertise in process development/optimization for digital twin, surrogate and reduced
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manufacturing, process physics, thermodynamics, and/or metallurgy to interpret sensor data in a materials science context. An excellent record of productive and creative research demonstrated by publications
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background which can be applied to conduct research analysis on advanced manufacturing technologies and manufacturing systems that could achieve transformative gains in process productivity and enhance
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scientific discovery Hands-on expertise developing and applying machine learning for materials and/or process discovery, particularly quantum and/or microelectronic materials Expertise in using or