This studentship is jointly funded by EPSRC and the School of Mathematical & Physical Sciences, University of Sussex.
The project in detail:
Dynamic networks are ubiquitous in nature and arise as a result of the interaction and feedback between processes taking place ON the network and the dynamics OF the network itself. Both are inherently coupled where the topology of the network influences the dynamics on the network, while the state of the nodes and/or links can determine whether nodes and/or links are activated, deleted or whether links rewire. Characterising the global behaviour of such systems is via bifurcation analysis that can be carried out by direct numerical simulation of the full system or analytically using a system of ODEs that provide a good approximation to the stochastic process.
The objective of the project is twofold. First, you will carry out a systematic study of the effectiveness of pairwise and effective-degree-type models in capturing the dual dynamics, and will determine their validity, depending on the type of dynamics on the network (i.e. epidemic and neuronal activity) and the dynamics of the network (e.g. random and link-type dependent link activation-deletion). In parallel, you will make the first steps in mapping the well-established concept of bifurcations from dynamical systems to bifurcations in network structure with the aim of providing a fuller global picture of the system and network behaviour.
The successful candidate will join the growing group of Mathematics Applied to Biology with considerable expertise ranging from Mathematical Epidemiology to Developmental Biology, and an active group of 3 PhD students in Dr Kiss’s team working on closely related topics.
The project will be jointly supervised by Dr Istvan Z. Kiss (Principal supervisor, Mathematics) and Dr L. Berthouze (Co-supervisor, Informatics). Further collaborators include Dr Péter L. Simon from Institute of Mathemtics, Eötvös Loránd University Budapest, Hungary.
A Research Training Support Grant is available for additional training and visits to conferences.
The successful applicant will be expected to undertake 60 hours per year teaching undergraduate students in the Department of Mathematics, as a condition of the award.
Award amount
£13726 tax-free maintenance bursary plus UK/EU fees waived for 3.5 years.
Eligibility
Due to funding restrictions, only UK and EU residents are eligible.
UK residents are eligible for full awards, including fees and maintenance.
EU residents are eligible for awards covering fees only, but EU students who have studied in the UK for the previous three years may be eligible for a full award. For a precise statement of eligibility, please consult this EPSRC web page: http://www.epsrc.ac.uk/skills/students/help/Pages/eligibility.aspx
We are looking for an academically-strong UK or EU Mathematics/Physics graduate with a first class degree or equivalent. You must have demonstrable experience in (1) mathematical modelling of biological processes (both deterministic and stochastic) and (2) programming (e.g. C/C++ or Matlab). Previous knowledge or exposure to network/graph theory or numerical computation/simulation with or on networks is desirable.
How to Apply
Apply through the Sussex on-line postgraduate application system via the Apply button below.
In the Other Information/Funding Section state that you are applying for “The EPSRC PhD studentship on bifurcations in system behaviour and network structure with Dr Istvan Kiss”.
Send an email to Dr Istvan Kiss (i.z.kiss@sussex.ac.uk)to confirm that you have applied on-line for this award.
Timetable
We would prefer the successful applicant to start January 2014 or May 2014. The very last date we can consider applications is 1st September 2014 for a late September start.
Early application is advised because the studentship will be awarded as soon as a suitable candidate is found.
Contact details
Informal enquiries should be sent to Dr Istvan Kiss (Senior Lecturer), i.z.kiss@sussex.ac.uk or Dr Luc Berthouze (Senior Lecturer), l.berthouze@sussex.ac.uk
http://www.sussex.ac.uk/profiles/211073
http://www.sussex.ac.uk/profiles/201607Â