PhD studentship: Developing Computational Foundations of Fair and Stable Decentralised Markets

A fully funded PhD studentship for 3.5 years to start in October 2026. This project will investigate the computational foundations of decentralised trading, combining tools from algorithmic game theory, decentralised computing, and machine learning to explain how stable and equitable outcomes can arise when agents interact strategically in different informational environments. The primary aim is to develop decentralised algorithms that capture the best-response dynamics of market participants and to establish theoretical guarantees for when, and how quickly, they converge to stable outcomes. The research will explore trade-offs between fairness and efficiency, while also analysing how markets can degrade under selfish or adversarial behaviour through concepts such as the price of anarchy. The student will gain expertise in algorithmic game theory, complexity analysis, market design, and machine learning, joining a cross-disciplinary research environment at the intersection of computer science and economics, with potential opportunities for collaboration in both academia and industry.