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The Faculty of Engineering, Department Toegepaste natuurkunde en fotonica, Research Group Applied Physics is looking for a PhD-student with a doctoral grant. More concretely your work package, for
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tools. In this PhD position, you will investigate the use of logic-based methods to provide decision support for the process of designing electromechanical systems. Here, the focus is not on the system
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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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Directed Energy Deposition (DED) process for metallic components. The PhD candidate will focus on edge computing and the application of AI for data analysis and for identifying correlations with ground truth
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on income/ wealth, and are these characteristics related to social identity and socio-political attitudes? RQ2: Does education-based status lead to a sense of entitlement, the feeling that one’s opinion is
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operational employment. This doctoral research will thus leverage the power of graph neural networks – a novel ML architecture, capable of learning fundamental physical behaviour by modelling systems as graphs
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of structures, contributing to sustainability. The use of advanced dispersive features of elastic waves allows for sensitivity to different length scales and physical properties, enabling the early detection and
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models combining machine learning, and physics-of-failure (PoF) approaches using in-situ data • You work on projects independently • You will present your work at international conferences and
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prevent over-consumption of fatigue life while balancing optimal production. This doctoral research will seek to speed up physics-based simulations of wind turbine structural responses through machine