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. This position is part of the CDT in Net Zero Aviation, which offers a modular, cohort-based training programme with emphasis on innovation and impact, collaborative working and learning, continuous development
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supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system
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, intake design, and computational methods. The research will directly support the Net Zero ambitions and contribute to the UK’s strategy of global competitiveness in aero-engine technologies. It will also
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access to state-of-the-art facilities and a network of professionals in the field. The expected impact of this research will be the development of valuable insights into how advanced technologies can be
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part of the EPSRC Centre for Doctoral Training (CDT) in Net Zero Aviation, offering an integrated, multidisciplinary training programme focused on innovation, collaboration, and inclusive leadership. As
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existing experience. This position is part of the CDT in Net Zero Aviation, which offers a modular, cohort-based training programme with emphasis on innovation and impact, collaborative working and learning
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the CDT in Net Zero Aviation, which offers a modular, cohort-based training programme with emphasis on innovation and impact, collaborative working and learning, continuous development, active engagement
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part of the CDT in Net Zero Aviation, which offers a modular, cohort-based training programme with emphasis on innovation and impact, collaborative working and learning, continuous development, active
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strategies that can improve sustainability and resilience in decentralised manufacturing networks. A unique selling point of this project is the opportunity for collaboration with world-leading experts through
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Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel