About this role
Research themes: Cyber Security, AI, Decentralized Systems, Applied Cryptography
UK students
This 3.5-year PhD studentship is open to Home (UK) applicants. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£20,780 for 2025/26; subject to annual uplift), and tuition fees will be paid. We expect the stipend to increase each year.
We recommend that you apply early as the advert will be removed once the position has been filled.
As AI systems scale, privacy, security, and trustworthiness emerge as challenges. For instance, private data may be leaked during model training, and interactions among autonomous entities can lead to vulnerabilities. These concerns are amplified in decentralized AI and multi-agent systems, when multiple parties (e.g., human or agent) might interact without full trust in a centralized party.
This research project aims to develop cryptographic solutions and frameworks that secure AI systems, particularly in decentralized and distributed settings. The project will investigate how advanced and modern cryptographic protocols, such as zero-knowledge proofs, secure multiparty computation, homomorphic encryption, exotic signatures, and their post-quantum versions, can enable secure, privacy-preserving, verifiable, and trustworthy AI. This project will allow a PhD student to contribute to the intersection of applied cryptography, decentralized systems (e.g., blockchains), AI safety, and privacy, with potential impact across domains such as finance and healthcare.
Applicants are expected to have an MSc degree in computer science or other majors related to decentralized systems, AI, cyber security, cryptography, or mathematics.
Outstanding candidates with a Bachelor’s degree from a four-year undergraduate program are also encouraged to apply. Paper publication is not mandatory, but a high-quality publication is helpful to strengthen an application, particularly for overseas candidates seeking studentship funding at the University of Manchester.
To apply, please contact the main supervisor Dr Zhipeng Wang - [email protected]. Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project.