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research with numerical modelling. The group also has a strong track record in data-driven modelling of unsteady flows. This project explores how paired floating vertical-axis wind turbines can enable wind
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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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behaviour in Luxembourg and beyond. EMUP will employ a data-driven approach and state-of-art methodologies to support decision-making for an optimal and smooth integration of the e-mobility sector, with
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steel and cemented carbides Conducting the previously defined experiments in lab and production environment on Laser welding machines Optimizing testing procedures and conducting testing
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the field.Vacancy 1: PhD (4 years) on experimental and numerical characterization of composites processing for hydrogen tanks[Net salary (after taxes) starting from 2600 EUR/month]Belgium has been taking a leading
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with privacy by developing techniques that optimize both aspects. The candidate will perform the work together with a team of postdoctoral researchers who are experts on the field and other PhD student
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Optimized Design and Control of Soft Aerial Manipulators), in collaboration with INRIA Lille Nord-Europe in France and its leading Defrost team in soft robot simulation and control, see https
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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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for wind turbines, with the ultimate objective of including structural health information in windfarm asset management to optimise structural lifetime consumption while guaranteeing optimal power production
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your knowledge and skills on state-of-the-art in machine learning, (probabilistic) modelling, system identification and numerical optimization. How to apply Send your CV containing one or more references