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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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reliability and connectivity techniques for multi-orbit satellite systems. In particular, the position holder will be required to perform the following tasks: Contribute to the design and performance evaluation
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materials to fabricate copper/carbon composites. The candidate will assist (explore @ lab scale but also work on industrial upscaling) with the production of the materials, enhancement of the existing
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31st October 2025 Languages English English English The Department of Geosciences has a vacancy for a PhD Candidate in Efficient Reservoir Simulation and Optimisation of Large-Scale CO₂ Storage
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9 Oct 2025 Job Information Organisation/Company Technical University of Denmark - DTU Department DTU Wind Department of Wind and Energy Systems Research Field Engineering Researcher Profile First
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
We are pleased to announce a self-funded PhD opportunity for Quantitative assessment of damage in composite materials due to high velocity impacts using AI techniques. Composite materials, such as
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Doctoral Network SCARPA in shaping the future of circular and sustainable footwear. As a PhD candidate, you will contribute to developing a better understanding of the compositional knowledge of shoes
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Project Description: Within aircraft jet engines, high-pressure turbine (HPT) blades are exposed to combustion gases requiring complex cooling strategies. Prediction of turbine heat transfer is critical, to ensure expected engine performance is achieved. To predict this complex flow and heat...
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. Composite materials often exhibit low fracture toughness values, yet various experimental techniques can enhance the toughness of thermoset and thermoplastic composites. Typical approaches include surface