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Disordered Systems

The Disordered Systems group at King's is at the forefront of research in statistical mechanics of disordered and complex systems.

The group's research concentrates on the development of new methods to tackle both fundamental issues, for example in non-equilibrium systems, and a broad range of applications to complex systems of many interacting units. The latter include mathematical systems biology and quantitative medicine (protein, metabolic and immune networks & network ensembles) with links to the Institute of Mathematical and Molecular Biomedicine as well as links with statistics and informatics in the area of Bayesian statistical inference and machine learning. The group also has a strong profile in soft condensed matter physics (rheology, polydispersity), glasses and driven non-equilibrium systems. Recent work has led to the development of new models to describe natural and social phenomena, such as systemic risk and catastrophic breakdown in complex systems, with applications to finance and the prediction of power outages. Random matrix theory has become an increasingly important area, studied using extensions of methods for sparse networks.

The group runs the MSc Complex Systems Modelling in collaboration with the Financial Mathematics group and the Departments of Informatics and Physics.

For PhD positions within the Disordered Systems group, please submit an application for Applied Research MPhil/PhD.


Group leads


Yan Fyodorov

Chair in Disordered Systems