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-efficient, open-loop optimisation of fermentation control profiles, building on recent theoretical developments in optimal control theory, reinforcement learning and numerical methods as well as laboratory
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with numerical experiments Communicate results through publications and presentations You should have a background in one or more of the following areas: Systems and Control Optimization / Operations
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and validated numerical models, to enable lightweight, reliable, cost-efficient, and sustainable novel design concepts. The PhD will also explore additively manufactured (AM) concepts with strong
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complex materials simulations. These agents will assist with setting up, executing, and optimizing electronic structure workflows, from standard ground-state Density Functional Theory (DFT) calculations
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design and integrity management of the support structure of the subsea HVDC electrode unit, supported by experimental tests and validated numerical models, to enable lightweight, reliable, cost-efficient
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-on experimentation with advanced digital fabrication, numerical modelling, material testing, and process optimization. You will work on the fabrication and mechanical characterization of composite specimens with
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in a variety of lossy media. The project will give you an opportunity to work with theoretical, numerical and experimental aspects of machine learning assisted design of antennas and metasurfaces