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This PhD opportunity at Cranfield University invites candidates to pioneer research in embedding AI into electronic hardware to enhance security and trustworthiness in safety-critical systems
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still guarantee system performance and safety? What new security features are needed to enhance the resilience of the controlled system? To analyse and design complex systems in a feasibly scalable way
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the major research gaps for eVTOL’s EMS, including 1-Inability of Rule-based EMS to guarantee optimal performance (doi.org/10. 3390/aerospace902011), 2- Violations with the constraints and missing safety in
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This PhD opportunity at Cranfield University invites candidates to explore the integration of AI into certification and lifecycle monitoring processes for safety-critical systems. The project delves
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Project title: Privacy/Security Risks in Machine/Federated Learning systems Supervisory Team: Dr Han Wu Project description: In the wake of growing data privacy concerns and the enactment
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thresholds. The project will also explore potential processing or environmental factors influencing toxin presence, contributing valuable insights to the food safety knowledge base. Cranfield University is a
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participation and transparency. As digital technologies become increasingly central to the delivery of these services, ensuring their security and resilience is more vital than ever. From digital identity and
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of the applications of the research topic, there is potential that the PhD researcher may engage in collaborations that are sensitive. Therefore, applications are restricted to those that are able to gain security
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directly addresses one of the most pressing challenges in modern information security: the malicious use of synthetic media. The relevance is acute, as deepfakes and AI-powered phishing campaigns are being
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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