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models in Argonne’s GREET model and related analytical tools. The appointee will evaluate current and emerging production pathways, including lithium production from brines and hard-rock resources, lithium
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learning (ML) to address future physics and detector challenges. Current physics interests include Standard Model measurements and searches for new phenomena. We welcome applicants who are excited
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(typically completed within the last 0-5 years) in Chemistry, materials science or related field. Knowledge and hands-on experience in the following areas: organic chemistry and synthesis. Experience in flow
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assess vehicle technologies to quantify energy consumption, performance and cost benefits. In this role, a successful candidate will perform vehicle modelling and simulation of advanced powertrains
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applied research on AI-driven and AI-enhanced industrial energy systems optimization modeling, material flow analysis, and supply chain analysis of industrial commodities and critical materials
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, characterizing mass transfer and selectivity under flow conditions, and screening and tuning DES compositions to optimize solubility, speciation, and electrochemical accessibility for target elements
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experimental results and contribute to high-impact scientific publications and conference presentations. 5. Demonstrated interest in, and commitment to staying current with, advances in quantum materials
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to current MSR developers for use in developing molten salt fuel specifications. Develop novel and improved methods for measurements of molten salt properties and standardize procedures to ensure quality data
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optimization schemes. From developing AI models to uncover structure-function relationships with limited data sets, to building automated electrode-electrolyte interface discovery workflows and implementing full
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beyond the Standard Model, including effective field theories and perturbative QCD, phenomenology at current and future colliders, as well as emerging areas in Artificial Intelligence, Machine Learning