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and life-cycle assessment will broaden your professional network while a dedicated training budget allows you to attend specialised courses—such as drone photogrammetry or advanced bioinformatics—and to
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challenge in the UK's Net Zero transition. Current satellite dependent navigation remains vulnerable to interference, jamming and signal degradation, causing serious problems for safe and efficient transport
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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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researcher with expertise in communication, project management, and leadership. You will build a robust national and international network and acquire advanced knowledge essential for implementing critical
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modelling software. Practical experience in advanced manufacturing techniques for novel materials. Opportunities to present research at international conferences and build a professional network across
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at international conferences and build a professional network across academia and industry. Development of expertise in cutting-edge experimental techniques, computational modelling, and interdisciplinary
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professional network spanning academia, industry, and national research centres. Through this multidisciplinary project, the student will develop expertise in: Contribute to the development and operation of
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. Cranfield Doctoral Network Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network
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are also Disability Confident Level 1 Employers and members of the Business Disability Forum and Stonewall University Champions Programme. Cranfield Doctoral Network Research students at Cranfield
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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