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relevance. A digital twin framework for safe, simulation-based validation before deployment in operational wind farms. Develop explainable AI (XAI) frameworks and human-computer interfaces that enable wind
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collaborate in a multi-disciplinary environment. It aims to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and
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to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events alongside our Doctoral Researchers Core Development
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Resilience (WIRe) , a prestigious collaboration between Cranfield University, the University of Sheffield, and Newcastle University. The WIRe programme offers bespoke training that hones both technical and
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would suit candidates with a sound background in engineering, computer science, or related disciplines. Funding This is a self funded opportunity. Find out more about fees here. Diversity and Inclusion
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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing and emerging applications, such as multi-domain autonomy and aerial mobility. With rising risks to...
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are part of the programme. The research is funded by the Centre of Propulsion and Thermal Engineering at Cranfield University. The work will be conducted at the Cranfield icing wind tunnel (IWT) based
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critical to ensuring the longevity and safety of fusion reactors. This PhD project focuses on developing an integrated framework that combines cutting-edge computational models, including Monte Carlo
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should have an equivalent of a 1st or 2:1 UK honours degree or MSc degree (Distinction/Merit) in engineering, computer science, or other closely related fields. Experience with ROS and proficient
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benefit from an enhanced stipend of £25,726 per annum, undertake an international placement, and complete a bespoke training programme within a cohort of up to 15 students. Students will benefit from being