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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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. The PhD researcher will also closely work together with the other doctoral and postdoctoral colleagues that work on composite hydrogen tanks and (micro-)mechanical characterization of composites, to form a
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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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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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monitoring of different sources of N fluxes in the system. He/she will need to contribute to the optimization and implementation of advanced sensing platforms for the collection of data on soil N, more
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/she will need to contribute to the optimization and implementation of advanced sensing platforms for the collection of data on different forms of nitrogen, more specifically nitrogen in manure and bio