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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 13 days ago
professionalism, enhance learning, 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
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characterization and optimization Development and operation of continuous fermentation processes under strict anaerobic conditions Strategic contribution to platform development for metabolic engineering What you
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following requirements: PhD in chemical sciences, biological sciences or materials engineering.Obtaining a doctoral degree within maximum 7 years from the announcement of the competition. They fulfilled
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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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Internal Number: JR89928 Position Summary This position will primarily support the implementation of a newly funded National Institute of Mental Health R01 grant focused on optimizing a digital chatbot
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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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project. The overarching aim of this project is in the development of new knowledge and a new framework to facilitate the optimal design and life-long adaptation of civil infrastructure systems
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signal processing algorithms on FPGA, optimized to significantly improve the resolution of real-time energy measurements made by the ATLAS Liquid Argon Calorimeter system. Use novel high-level synthesis
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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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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