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Field
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qualifications needed (particularly the habilitation), and as a chance to develop a distinct, visible research profile within the academic community. Completed domestic or foreign doctoral/PhD studies in the field
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characterization of electrode materials Design, operate and optimize electrochemical reactors and separation systems, analyze and interpret data using electrochemical and materials characterization techniques (e.g
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through long-term impact assessment and optimization. The goal is to develop a framework to estimate carbon emissions across AI's development, operation, and use. This framework enables stakeholders
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optimized, you will apply the technique to solve open questions on the structural transformations occurring in batteries during cycling. The preferred starting date is 1 December 2025. Profile You hold a PhD
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
, and create personal and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISION Our vision is to be
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We invite applications for a Postdoctoral Appointee to contribute to a growing research program in process systems modeling and optimization for clean energy, critical materials, and advanced
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related to a biomedical field. Preferred Qualifications: - Advanced degree (PhD) in biomedical sciences or related field(s) - Experience carrying out complex, long-term research projects. - Experience with
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, testing, and demonstration of novel CCUS technologies Process simulation, cost, life cycle, and social assessment of CCUS value chains Reactor design, optimization, and sizing using phenomenological and/or
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testing, and advanced process simulation, with the objective of optimizing grinding performance and enhancing resource recovery. The ideal candidate will have a strong background in mineral processing
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of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict ore quality and optimize operational decisions. 2. Key Responsibilities