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. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical engineering, materials science, civil engineering, structural engineering, or a closely
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and technologies, and in advancing data-driven risk monitoring approaches for supply chain resilience. The candidate will conduct comprehensive supply chain mapping, modeling, and analysis—integrating
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primary goal of this work is aimed at advancing next-generation, lithium-ion technology through a detailed understanding and mitigation of surface degradation mechanisms that limit state-of-the-art lithium
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facilities with relevance to critical materials and nuclear reprocessing Analyze data, prepare manuscripts for submission to peer-reviewed publications, prepare technical reports for sponsors, and attend and
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Requirements Required skills, abilities, and knowledge: Recent or soon-to-be completed PhD (within the last 0-5 years) by the start of the appointment in computer science, electrical engineering, applied
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, experience in scaleup is a plus. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in chemistry and/or closely related discipline. Expertise in the study
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monitoring and gradient tests. Participate in training opportunities, including attending the US Particle Accelerator School (USPAS). Position Requirements PhD completed in the past 5 years or soon to complete
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will receive full consideration. Key Responsibilities AI-ready data and analysis for the ePIC Barrel Imaging Calorimeter and our Jefferson Lab program Support for the PRad-II and X17 experiments
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-completed PhD with strong background in Materials Science or Physics (within the last 5 years) Considerable experience in understanding magnetic-domain physics in thin film and/or nanostructured materials
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Because of the drastically increasing demand from AI/ML applications, the computing hardware industry has gravitated towards data formats narrower than the IEEE double format that most computational