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range of resources available. At a glance Application deadlineOngoing Award type(s)MSc by Research Duration of awardOne year full-time, two-three years part-time EligibilityUK, EU, Rest of world
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and emerging applications, such as multi-domain autonomy and aerial mobility. With rising risks to PNT systems from interference, spoofing, and cyber-physical attacks, unified, security-aware integrity
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recycling programs, resource allocation, and waste management. By enhancing decision-making, it will foster more resilient economies and contribute to sustainable circular practices, ultimately reducing
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. In order to apply please send a copy of your CV to Jon Kett-Reynolds, Centre Manager, to j.kettreynolds@cranfield.ac.uk Closing date for receipt of applications: 19 October 2025
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infrastructure. However, the increasing application requirements and rising threats from intentional interferences, spoofing, and cyber-physical attacks expose vulnerabilities in conventional GNSS-centric systems
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that we reserve the right to close this advert prior to the stated closing date should we receive sufficient numbers of applications. Therefore, we would encourage you to complete and submit your
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sensors to deliver resilient, high-accuracy positioning. The project sits at the intersection of navigation, AI-enhanced signal and data analysis, and wireless communication systems, with applications in
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Design and Manufacturing Engineering to Tackle Global Sanitation Challenges - MSc by Research or PhD
of the Stonewall Diversity Champions Programme. We are committed to actively exploring flexible working options for each role and have been ranked in the Top 30 family friendly employers in the UK by the charity
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. These are directly applicable to roles in offshore engineering, digital safety systems, renewable energy consultancy, and academia. At a glance Application deadline26 Nov 2025 Award type(s)PhD Start date26 Jan 2026
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
complex engineering data and deliver insights that are robust, adaptable, and applicable across complex, high-value, safety-critical domains. This research will contribute to shaping the next generation of