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-house database of experimental real-world data enabling large-scale validation of developed algorithms. Wind turbine drivetrains are critical components, and their failures can lead to significant
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The Faculty of Engineering, Department Elektronica en informatica, Research Group Electronics and Informatics: Research – Development - Innovation is looking for a PhD-student with a doctoral grant
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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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set a course for the future – a future that you can help to shape. The EMAT research group at the Faculty of Science (University of Antwerp) is seeking to fill a PhD position on the development
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and grippers offer improved safety and adaptability but introduce new challenges in design and control. Their development is still largely bio-inspired and trial-and-error based. Integrating flight and
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for space logistics. With the development of mathematical models and optimisation algorithms, we aim to support strategical, tactical and operational decisions in the context of the deployment of in-orbit
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. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop machine learning surrogates of wind energy systems. As newer
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radar-based sensing. You will develop adaptive algorithms that dynamically select the optimal radio configuration based on the specific requirements of each application. The radio platform supports a
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, storage and demand. YOUR TASKS You will develop mathematical models and metaheuristic algorithms for complex optimization problems in the context described above, see e.g., https://arxiv.org/abs/2503.01325
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learning algorithms. The two PhD students hired through this vacancy will primarily contribute to the development of debiased learning methods and assumption-lean modeling tools, and their application