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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