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This self-funded PhD opportunity explores assured multi-sensor localisation in 6G terrestrial and non-terrestrial networks (TN–NTN), combining GNSS positioning, inertial systems, and vision-based
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filled. This fully funded PhD explores AI-native and sensing-aware wireless systems where communications and sensing are co-designed end-to-end. You will unify modern machine learning, statistical signal
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trust in digital communications and readily bypass conventional security controls. This PhD research proposes to design, develop, and validate a novel, explainable, multi-modal detection framework. By
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management experience across multiple industries, build an extensive professional network spanning academia and industry, and cultivate commercial awareness that enhances your career prospects. Alumni from
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of the student’s project and allow them to network. The partners will also be able to offer the PhD student the opportunity of placements, during which the student can gain major insights. This would help them
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, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from nonlinear control and optimisation
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engineering, computational neuroscience, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from
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Thermoacoustics of net-zero swirl stabilised premixed hydrogen combustors Award Summary 100% fees covered for Home students, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI
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merit or above in a relevant subject area. If your first language is not English you need an overall IELTS of 7.0 (with a minimum of 6.5 in writing, and 6.0 in all other sub-skills). The successful
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or Stata (or similar packages) would be an advantage, although training will be provided. Strong written and verbal communication skills are essential. The project is based in the Net Positive Centre’s hub