Fully Funded PhD in Secure and Trustworthy AI for Autonomous Vehicle Ecosystems University of Southampton in United Kingdom

Fully funded PhD opportunity at the University of Southampton in Secure and Trustworthy AI for Autonomous Vehicle Ecosystems.

This project sits at the intersection of computer science, cyber security, artificial intelligence, machine learning, and robotics/autonomous vehicles. The research will develop AI-enhanced threat-modelling techniques to improve the cybersecurity and resilience of autonomous vehicle systems. Topics include adversarial attacks, data poisoning, sensor manipulation, model interference, formal multi-dimensional threat modelling, AI-driven threat intelligence, anomaly detection, and mitigation strategies for safety-critical systems.

The project is supervised by Dr Erisa Karafili, Associate Professor at the University of Southampton, whose research interests include formal methods for security problems, cyber attack attribution and investigation, and threat models for IoT devices and hybrid systems.

Funding is an IDLA EPSRC studentship with an industrial partner. It is fully funded, including tuition fees and an enhanced stipend above the UKRI minimum, plus support for travel, equipment, and laboratory consumables. The project also includes an industrial placement with a global automotive manufacturer.

Eligibility is restricted to UK and Horizon Europe students only. Applicants should have a first-class honours degree or equivalent in cyber security, computer science, artificial intelligence, engineering, or a closely related discipline. Strong programming skills, a solid background in cyber security and AI/ML, and interest in autonomous vehicles and safety-critical systems are required; experience with adversarial machine learning is desirable.

Deadline: 19 June 2026. Applications may close early if a suitable candidate is found, so early application is encouraged.

How to apply: use the University of Southampton PhD application portal, choose Research / 2026/27 / Faculty of Engineering and Physical Sciences, select PhD Computer Science (7089), and add the supervisor name in section 2. Submit a research proposal, CV, two academic references, transcripts/certificates, and English language qualification if applicable.