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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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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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individually, make a real difference. The role The Computer Science Research Centre at the University of Surrey is seeking to recruit a research assistant in the field of applied cryptography and secure systems
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(coordination) and safety constraints can be intractable. Your work will bridge this gap by providing generalizable, provable design approach that apply across a wide range of networked systems. This 3.5-year PhD
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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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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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Sodium-ion batteries are rapidly emerging as a powerful alternative to lithium-ion systems—offering significant advantages in cost, sustainability, and safety. To unlock their full potential
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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are promising sustainable alternatives to lithium-ion systems, leveraging abundant, low-cost materials (Na, Fe, Al, biomass-derived carbon). However, a major bottleneck is the instability of the SEI formed during