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achieving Net Zero by 2050. In partnership with Plant Health at Defra (Department for Environment, Food & Rural Affairs), this project introduces a novel AI-driven framework to protect the nation’s plant life
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and communication skills. Funding Self-funded/partially funded Please contact the supervisor for more information or explore our funding finder . Cranfield Doctoral Network Research students
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justice and inequality in the context of the United Kingdom. As community engagement is central to this research, we particularly encourage applications from candidates with strong existing networks with
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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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Social Sciences, and the Northern Advanced Research Training Initiative network. The award is available to home and international candidates. If English is not the candidate’s first language, the candidate
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The Medicines And Healthcare Products Regulatory Agency; | Canary Wharf, England | United Kingdom | about 1 month ago
communication skills with experience in presenting research, writing study protocols, and drafting strategic papers and manuscripts for publication. Actively build and maintain a network of colleagues and
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Anglia) and to present their results to wide-ranging audiences in conferences and meetings. The multidisciplinary nature of this project will contribute to build a broad network and will provide
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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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networks continuously generate sensitive data. You will investigate adaptive learning frameworks – such as multi-agent or multi-task approaches – that ensure robustness, explainability, and trust across
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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