Large Language Models (LLMs) such as GPT-4 and Claude have revolutionised how we generate, search, and interact with information. However, their growing capability also raises critical privacy and security concerns. Trained on vast datasets, LLMs may inadvertently memorise and reveal sensitive personal or confidential information, creating new forms of privacy leakage.
You'll investigate how such risks emerge and develop techniques to mitigate them, including machine unlearning to remove unwanted training data influences and differentially private fine-tuning to ensure formal protection guarantees. You'll also explore how the rise of Retrieval-Augmented Generation (RAG) and agentic AI systems, which allow models to access external data and act autonomously, introduces new layers of vulnerability and accountability challenges. The aim is to build a comprehensive understanding and practical framework for auditing and safeguarding LLMs across their lifecycle.
This project will be carried out within an interdisciplinary team spanning Law, Finance, Human-Computer Interaction, and industry experts in AI governance and cybersecurity, offering a unique opportunity to conduct impactful, real-world research at the intersection of technology, ethics, and regulation.
Entry requirements:
You must have a UK 2:1 honours degree, or its international equivalent.
You must be proficient in Deep Learning. Familiarity with tools such as PyTorch will be advantageous.
Fees and funding:
Full scholarships include tuition fees, a tax-free stipend at the UKRI rate for up to 3.5 years (totalling £20,780 for 2025/26, rising annually). UK, EU and Horizon Europe students are eligible for scholarships. Chinese Scholarship Council funded students are eligible for fee waivers. Funding for other international applicants is very limited and highly competitive. Overseas students who have secured or are seeking external funding are welcome to apply.
How to apply:
Apply now
You need to:
- choose programme type (Research), 2026/27, Faculty of Engineering and Physical Sciences
- select Full time or Part time
- search for programme PhD Computer Science (7089)
- add name of the supervisor in section 2 of the application
Applications should include:
- research proposal
- your CV (resumé)
- 2 academic references
- degree transcripts and certificates to date
- English language qualification (if applicable)
