Completed Mathematics & Statistics

Bristol Centre for Complexity Sciences

In plain English

AI plain-English summary

The Bristol Centre for Complexity Sciences will train a new generation of researchers to tackle problems that emerge when many interacting parts—cells in a tissue, vehicles in a city, molecules in a reaction—produce behaviour that cannot be predicted from any single component alone. This matters because the UK lacks enough scientists who can work across biology, chemistry, and engineering to address these "complex systems" problems. Traditional academic training keeps disciplines separate, but real-world challenges—such as how a drug moves through a living network, how a power grid stays stable, or how a chemical factory avoids cascading failures—require people who can build mathematical models and run simulations that connect the pieces. If the centre succeeds, it will produce a steady pipeline of researchers who can move between theory and application. They might help design more resilient infrastructure, improve drug discovery, or make manufacturing processes less prone to unexpected breakdowns. The work is fundamentally about building the intellectual toolkit and the trained workforce needed to understand systems that are too complicated for any single field to solve alone.

View original technical description
The Bristol Centre for Complexity Sciences (BCCS) will meet the present national need to address the implications of Complexity within the cognate applications areas of Engineering, Life & Molecular Sciences by setting up an integrated multidisciplinary research and training environment in complexity science. The selected application areas in aspects of biology, chemistry and engineering offer major challenges to complexity but their resolution requires innovative theory to be developed. The vision for the BCCS is that it will grow a dynamic hub of theoretical and computational expertise that interacts with and connects the application areas, which in turn link to cross-cutting University research themes.

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Researchers

Stephen Hogan (Principal Investigator)

Related Research

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Original classification

Training Grant

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.