Anticipatory characteristics of nonlinear complex systems dynamics

Department/School: Biomedical Engineering, School of Biological Sciences

Supervisor: Professor Slawomir Nasuto

Co-supervisor: Dr Yoshikatsu Hayashi

Application Deadline: Applications accepted all year round

Funding Availability: Self-Funded PhD Students Only

Duration: 36 months


The ability to react in response to future possibilities rather than being passively and deterministically driven by the past and current state is a fundamental characteristic of natural cognitive systems. It appears even in the simplest organisms, suggesting that it arises from a particular way such systems are dynamically coupled to their environment. Such coupling mechanisms may be generic and hence may also characterise anticipatory mechanisms that appear in the nervous system.

The project will look at models of dynamical couplings in complex systems giving rise to anticipatory characteristics and will investigate their properties. Characterisation of such anticipatory mechanisms will give rise to new predictive data analysis tools, which will reflect these predictive characteristics and hence can be used in practical applications in which forecasting plays an important role. The project will evaluate such models and the resulting analytic tools using neural data which will provide both the source of potential natural anticipatory mechanisms as well as data forecasting benchmarks. Of particular interest are projects with a focus on dynamics of cultured neural networks, or EEG activity with a view towards Brain Computer Interface applications.

University of Reading

The University of Reading is one of the UK’s 20 most research-intensive universities and among the top 200 universities in the world. Achievements include the Queen’s Award for Export Achievement (1989) and the Queen’s Anniversary Prize for Higher Education (1998, 2006 and 2009). This project will take place in the Biomedical Engineering Section, School of Biological Sciences, which has a strong reputation for its innovative research in computer science, cybernetics, and electronic engineering.


Applicants should have a bachelors (at least 2.1 or equivalent) or masters degree in physics, applied mathematics, engineering, or a strongly related discipline. Strong analytic and programming skills are preferable. Experience in dynamical systems, complex networks and experimental data analysis are desirable.

How to apply

Please submit an application for a PhD (initial registration) in Cybernetics (Biological Sciences) to the University using the link below.

In the online application system, there is a section for “Research proposal” and a box that says “If you have already been in contact with a potential supervisor, please tell us who” – in this box, please enter “Professor Slawomir Nasuto”.

Funding notes

We welcome applications from self-funded students worldwide for this project.

Further enquiries

For further information about this PhD opportunity, please contact:

Professor Slawomir Nasuto, tel: +44 (0)118 378 6701,

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