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investigate strategies to enhance communication security, focusing on resilience against jamming and spoofing attacks. Students will work on designing secure architectures that ensure data integrity and system
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their operational lifespan. A key aspect of the project will be the incorporation of communication security measures, specifically targeting resilience against jamming and spoofing attacks. Students will investigate
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
placement with Rolls-Royce. The research focuses on AI-driven digital twins, using large language models and knowledge graphs for predictive maintenance in aerospace systems. Aerospace systems generate vast
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their full potential. At Cranfield, we value our diverse staff and student community and maintain a culture where everyone can work and study together harmoniously with dignity and respect. This is reflected
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researcher with wider transferable skills (communication, project management and leadership) with an international network of colleagues. At a glance Application deadline23 Jul 2025 Award type(s)PhD Start
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This fully-funded PhD studentship, sponsored by the EPSRC Doctoral Landscape Awards (DLA), Cranfield University and Spirent Communications, offers a bursary of £24,000 per annum, covering full
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all doctoral candidates to thrive and achieve their full potential. At Cranfield, we value our diverse staff and student community and maintain a culture where everyone can work and study together
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Models (LLMs). Orchestrating AI/ML pipelines in 6G. Developing certification and checking processes for code inside ORAN 6G. The research will be a combination of software engineering, radio
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year. The student will have the opportunity to join a vibrant community and team of researchers. They will develop important technical skills in spacecraft structural dynamics, controller design, and
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analytics tools have been massively developed in the research community to address this challenge. These AI-based analytics tools are data-driven and black-box, so the interpretation of how predictions