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machine learning expertise, with the goal to enhance predictive capability and scalability of multi-scale and multi-physics simulation codes. Perform high-fidelity CFD simulations of complex physical
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related field at the PhD degree level with zero to three years of experience or equivalent in the scientific application of this knowledge and practical laboratory experience. To perform the essential
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to state-of-the-art research facilities and gain in-depth knowledge of the research frontiers of in situ characterization of deposition science and electrochemical interfaces. Position Requirements: A PhD in
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to develop, synthesize, characterize and electrochemically evaluate next generation cathode materials for lithium-ion and sodium-ion batteries. Position Requirements Recent or soon-to-be-completed PhD
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achieved through a formal education in chemical engineering, mechanical engineering, or a related field at the PhD degree level with zero to five years of experience or equivalent in the scientific
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in high-voltage battery systems through a fundamental understanding of interfacial mechanisms. Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in Organic Chemistry
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modeling of crystals, dislocation dynamics, and defect analysis, linking atomic-scale simulations to macroscopic properties. Familiarity or interest in machine learning methods and computing frameworks
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encompass: Catalysts Synthesis: Utilize your expertise in materials synthesis to develop novel catalysts guided by machine learning algorithms Catalyst Performance Evaluation: Utilize aqueous electrochemical
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transfer of the reaction process. This research is closely aligned with the corresponding experimental studies. Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field
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-impact, interdisciplinary research. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years in chemical engineering, mechanical engineering, process systems