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Field
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providing quality control or process optimization for electron microscopy in an industrial environment. Experience bringing electron microscopy to industrial application. Experience leading projects
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/ Robust) Combinatorial Optimization, Game Theory, and Network Theory, as well as Artificial Intelligence. Potentially, scenarios could be simulated using agent-based, discrete-event, or other techniques
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consumption while guaranteeing optimal power production. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop graph-based
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underground conditions. Apply machine learning and AI techniques to enhance model accuracy and optimize design parameters. Contribute to the development of a comprehensive, AI-based design methodology for LUS
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for optimizing metals microstructures in-situ during the AM process as well as ex-situ during post-AM treatments and enable predictions of the microstructural evolution, and thus changes in properties, while AM
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! We are inviting applications for a 4-year full-time PhD position as part of the SCOPE project—Shelf-life Control, Optimized Pricing, and Excess Redistribution—a collaboration between the Operations
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Application deadline: All year round Research theme: Systems and Control How to apply: uom.link/pgr-apply-2425 This 3.5 year PhD project is funded by The School of Engineering and is available