40 high-performance-computing-"University-of-Exeter" PhD positions at Cranfield University
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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profoundly affect their mechanical properties and overall performance. Therefore, understanding the temperature field and developing effective thermal control techniques are vital to ensuring a high-quality WA
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intelligent systems aim to optimize power usage without compromising performance, employing strategies like power-aware computing and thermal-aware optimization. These systems are crucial in extending
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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical
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significantly reduce the amount of vibration data to be stored on edge devices or sent to the clouds. Hence, this project's results will have a high impact on reducing the hardware installation and operation
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the computational inefficiencies of physics-based models and enabling faster, potentially more accurate predictions. However, AI models require substantial volumes of high-quality, labelled training data, which
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doctoral training programme dedicated to academic research in space propulsion. R2T2 PhD programmes are already underway at nine UK universities, and the programme overall is centred on the Westcott facility
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-box techniques in the industry is still high. One of the main reasons is that the performance of such techniques highly depends on a large amount of good-quality data. Unfortunately, the availability
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frameworks are critical to ensuring safe, resilient, and trustworthy navigation in transport and other domains. This project will aim to enhance the performance and robustness of autonomous navigation
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
based within the Manufacturing, Materials and Design theme at the Centre for Digital and Design Engineering (CDDE), which offers access to advanced simulation, visualisation, and high-performance