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Field
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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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-informed data analytics tools for the predictive maintenance (PdM) strategy applications to high-value critical assets. Among others, the recently developed Physics-informed Neural Network (PINN) technique
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Join our diverse and inclusive team to transform the future of aviation as part of the UK’s EPSRC Centre for Doctoral Training in Net Zero Aviation. Offering fully funded, multidisciplinary PhD
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reliable public transportation system. This project will give you access to unique field data and expert knowledge, and the opportunity to visit Network Rail and work with colleagues in Colombia. If you're
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and networking. They will be working within a vibrant community of research degree students and researchers at both institutes. The post-holder must have a relevant first (or postgraduate) degree in
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technological advances that support the global transition toward net-zero emissions and sustainable aerospace engineering. Motivation The reliability of electric propulsion systems is pivotal for next-generation
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to conduct 9 months of field research, often in the absence of running water, electricity, and network connectivity, and roads, and with simple meals. These environments require adaptability, cultural
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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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. Funding This is a self-funded PhD. Find out more about fees. Cranfield Doctoral Network Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and
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, including staff, students and industry partners, benefits from a close network of knowledge and opportunity exchange. Situated in Shropshire, the campus and the surrounding area provide an excellent working