PhD Studentship: Post-Quantum Zero-Knowledge Proofs and Trustworthy AI

Are you ready to help shape the cryptographic foundations of the next generation of trustworthy, quantum-resilient AI systems?

The School of Computer Science at the University of Sheffield is inviting applications for a fully funded PhD studentship offered in collaboration with the Defence Science and Technology Laboratory (DSTL), at the intersection of post-quantum cryptography, zero-knowledge proofs (ZKPs), and trustworthy AI.

This is a rare opportunity to work on a problem that sits right at the frontier of two of the most urgent challenges in modern computing: the looming threat quantum computers pose to current cryptographic infrastructure, and the growing need for AI systems whose outputs can be verified, audited, and trusted without exposing sensitive data or models.

This opportunity is primarily intended for candidates who qualify for UK home student rates. The studentship includes a competitive, tax-free stipend of approximately £25,000 per year, which exceeds the standard UKRI rates, and is subject to annual inflationary adjustments.

Research themes include:

• Designing efficient, lattice- or code-based zero-knowledge proof systems resilient to quantum attacks
• Verifiable and privacy-preserving machine learning (e.g. proving model integrity or fairness without revealing training data)
• Scalable ZK-proof constructions for federated and decentralised AI pipelines
• Formal security analysis of post-quantum ZKP protocols in real-world AI deployments

School of Computer Science at the University of Sheffield. A leading centre for security, machine learning, robotics, and autonomous systems. The student will join a research group working at the interface of advances in machine learning, security and post-quantum cryptography, with opportunities to collaborate with partners in robotics, autonomous systems and AI safety. Access to modern computing facilities and experimental platforms (e.g. robotic testbeds or simulators) will be available depending on the final focus of the work.

Defence Science and Technology Laboratory (Dstl). As the Ministry of Defence (MOD)’s in-government science and technology organisation, Dstl provides unique expertise, insight and innovation to maintain UK warfighting readiness in an increasingly dangerous and complex world. As MOD's science and technology leaders, Dstl provides expert advice, analysis, and capability across a wide range of applications, including robotics and autonomous systems, AI, and Data Science.

Eligibility and Desired Background

Applicants should hold (or expect to obtain) a first‑class or strong upper‑second‑class degree, or a Master’s degree, in a relevant discipline such as Computer Science, Applied Mathematics or a closely related field. A strong mathematical background and proficiency in programming (preferably Python) are essential. Prior exposure to one or more of the following: machine learning, information security, modern crypto systems will be an advantage.

Inquiries. Interested candidates are encouraged to contact Dr Prosanta Gope (p.gope@sheffield.ac.uk) or Dr Behzad Abdolmaleki (behzad.abdolmaleki@sheffield.ac.uk) by email with the subject line "Prospective PhD Students" to discuss the position informally and should include a brief CV detailing their suitability for the role.

For information on how to apply and what documents are required please see the University of Sheffield application portal here: https://www.sheffield.ac.uk/postgraduate/phd/apply. Please include a CV and covering letter with your application.

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