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Anticipatory characteristics of nonlinear complex systems dynamics

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  • Full or part time
    Dr Nasuto
    Dr Hayashi
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

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.

School of Systems Engineering, 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 School of Systems Engineering (SSE), which has a strong reputation for its innovative research in computer science, cybernetics, and electronic engineering.

How to apply:
(1) Submit an application for a PhD in Cybernetics using the link below.
(2) After submitting your application you will receive an email to confirm receipt; email should be forwarded along with a covering letter and full CV to Prof Slawomir Nasuto ([email protected]).
(3) 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 “Prof SJ Nasuto”.

Further enquiries:
Prof SJ Nasuto, email: [email protected]

Funding Notes

We welcome applications from self-funded students worldwide for this project.
Students from Brazil: we welcome and support applications for the Science Without Borders Scholarship (Ciência sem Fronteiras).

Eligibility:
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.

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