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Complexity science

Complexity science explores the emergent behaviour of complex systems by focusing on interconnections of the system components and systems architecture, rather than the individual components themselves. It represents a novel scientific approach across traditional discipline boundaries.

The EPSRC Complexity Science research area includes funding from all four capability areas - Mathematical Sciences, ICT, Engineering and Physical Sciences. New funding applications are processed by the most relevant Theme, with joint-funding across themes as appropriate.


This area has grown significantly in the UK over the past few years and the UK is now internationally strong, both in terms of underpinning theory and application to real world problems. In recent years, complexity science has been funded by the Cross-Disciplinary Interfaces programme which has coordinated a number of initiatives. These managed activities have led to a broad portfolio spanning the EPSRC capability themes;  Mathematical Sciences, ICT,  Engineering and Physical Sciences, as well as research in application areas, such as energy. The importance of the area is demonstrated by the International Review of Mathematical Sciences 2010 (IRMS 2010) landscape document, which highlighted the opportunities that complexity science presents to mathematics (in particular Non-linear Systems), and the links with physical sciences, engineering, computer science, biology and social sciences through application.

Complexity science has strong potential societal impact (e.g. applications in healthcare), it has potential economic impact (e.g. through links to finance) and it also has potential impact on many other areas of research. The vast array of application areas are demonstrated by the programmes for the annual European Conference on Complex Systems, and the background reports and projects funded through the Complexity-NET ERA-NET.

EPSRC investment in this area will be maintained, relative to other areas of the portfolio, in order that the UK can retain its international position. This will be achieved through standard application routes under the most appropriate theme. We will encourage proposals where underpinning theory is inspired by or strongly linked to applications. EPSRC has supported three Doctoral Training Centres in this area. We will monitor the career trajectories of the DTC graduates, and we will seek to support the very best DTC graduates as they progress through their careers through fellowships. The multidisciplinary nature of the area should be strengthened, for example by linking to Systems Engineering, and awareness of complexity science in related disciplines should be raised.

Current investments

For information on current EPSRC investments in this research area, please see Grants on the Web (GoW).

EPSRC investments on 01 April 2011

Complexity science is 11.8% of EPSRC's total investment in Mathematical sciences related research areas.

The proportion of funding in Complexity science by EPSRC theme on 1st April 2011.

Number of EPSRC Grants 1, 2 Value of Grants 1, 3
75 £25.5M
  1. Based on number and value of current grants (excluding training grants) on 01 April 2011.
  2. Grants are classified using one or more research area. The number of grants listed does not reflect the proportion assigned to different research areas and thus all grants of some relevance to the research area are counted.
  3. Grants are classified using one or more research area. The value of investment does reflect the proportion assigned to different research areas.

Current Major EPSRC Research Investments include:

  • Department of Computer Science, University of Bristol
  • School of Experiment Psychology, University of Bristol
  • Institute of Energy and Sustainable Development, De Montfort University
  • School of Social Sciences, University of Manchester
  • School of Social Sciences, University of Southampton
  • Sociology, University of Surrey
  • Centre for Advanced Spatial Analysis, University College London

EPSRC Centres for Doctoral Training of relevance