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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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efficient than digital computer and previous experimental implementations. This work is both experimental, numerical and theoretical in nature. You will be selected by the Applied Physics research group
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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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The Faculty of Sciences and Bioengineering Sciences, Department Computer Science, Research Group Federated labs AI and Robotics is looking for a PhD-student with a doctoral grant. More concretely
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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