30 parallel-computing-numerical-methods "DTU Electro" PhD positions at Cranfield University
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validation experiments for modelling • Computational fluid dynamics techniques • Finite element analysis method • Reviewing literature, planning and managing research, writing technical report / paper
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information from unintended data leakage. Communication Resilience Against Jamming and Spoofing: Develop AI-driven methods to detect and mitigate jamming and spoofing attacks, enhancing the robustness
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operability and performance. The project will build on previous successful programmes which have developed considerable expertise in the measurement of intake flow distortion using non-intrusive methods
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We are seeking a highly motivated candidate to undertake a PhD program titled "3D Temperature Field Reconstruction from Local Temperature Monitoring in Directed Energy Deposition." This exciting
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, compressible flow, aerodynamic analysis and optimisation would be an advantage. Broader experience of engineering computational modelling and optimisation methods would also be and advantage. As part of
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statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
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-the-loop testing, and advanced AI methods will further enrich the student’s research experience. The student will have the opportunity to join a vibrant community and team of researchers. This project will
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. The studentship is funded by the Leverhulme Trust through the Connected Waters Leverhulme Doctoral Programme. Urban blue networks, including rivers, canals and wetlands, are dynamic systems that shape how cities
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designing research approach and drawing on a wide range of social science methods. Key commercial sectors include (but are not limited to) data centres and high-tech industries, as well as food and beverage
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap