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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
-funded position. The selected candidate will collaborate with experts in diabetes research on two clinical trials aiming to optimize the implementation of evidence-based diabetes technologies among older
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progression of the disease and optimize treatments. The person will use these models to develop novel treatment strategies and determine the efficacy of targeted treatments using genomic information. They will
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the emphasis of the position will be on the development of nanomaterials for AM and understanding of AM process optimization, functional materials design and compositional grading, electrochemical and
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optimize epitaxial growth of complex oxide nanostructures, especially ferroelectrics, via solid-phase epitaxy (SPE) Perform thin-film and device characterization across structural (XRD, AFM, SEM, XPS, TEM
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optimization of pyrometallurgical flow sheets for the production of value-added materials or metals.The selected candidate will contribute to both fundamental understanding and industrial applications of thermal
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to academic excellence. Our research, creative activity and people positively impact the world. Like the city we call home, UB is distinguished by a culture of resilient optimism, resourceful thinking and
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. The selected candidate will contribute to an in-depth study of organic, colloidal, biological, and inorganic fouling mechanisms, the optimization of cleaning protocols (CIP – Cleaning in Place), and the
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of water intended for agricultural use. The selected candidate will contribute to the development and optimization of desalination processes (membrane-RO), the analysis of treated water quality (especially
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, working on the development of advanced AI/ML algorithms for battery management systems (BMS) in electric mobility and micro mobility applications. The primary focus will be on creating and optimizing state
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and