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Unifying multiscale brain network interactions (SAMIU19FMHMTH)

Project Description

Important: Applications for this project will open on the UEA system w/c 2 September 2019.

We offer a fully funded inter-disciplinary PhD project that focuses on the development of new mathematical models and their application in cognitive and clinical neuroscience. The project brings together several strands of statistical mechanics and non-linear dynamics with computational neuroscience to improve current mathematical models of healthy ageing and neurodegeneration.

This scheme attempts to bridge the gap between molecular biology and the complex disease syndromes by addressing an important missing link through unifying multi-scale brain network interaction. The project will allow the prospective PhD candidate to combine experimental work from functional MRI & EEG with computational models of healthy ageing and disease.

The work will require the prospective PhD candidate to actively collaborate with clinical and mathematical research groups at the University of East Anglia, and several research institutions.

Our Offer:
Engagement with international multidisciplinary teams in highly ambitious projects in an inspiring and collaborative environment.

Various opportunities for further education, training and professional growth.

Essential Criteria
Excellent programming skills, experience in at least one of the following: MATLAB, Python, Java/C++, and C/Fortran.

A solid background in statistical mechanics &/or non-linear physics/mathematics.

Excellent command of written and spoken English

Previous experience in areas of statistical mechanics, non-linear physics/mathematics, graph theory or signal processing (e.g., time series analysis) would be beneficial.

Knowledge of machine learning techniques.

For more info on the supervisors:
Dr Sami -
Dr Davide Proment -
Type of programme: PhD
Start date: Jan 2020
Mode of study: Full time

Funding Notes

This PhD studentship is jointly-funded by Norwich Medical School and the School of Mathematics. Funding comprises Home/EU fees and a stipend of £15,009 and £1000 per annum to support research training.

Entry requirements:
Acceptable first degree: B/MSc in Physics, Mathematics, Engineering, Computer Science.
The standard minimum entry requirement is 2:1. An MSc qualification will be advantageous


i) Sami, S., Robertson, E. M., & Miall, R. C. (2014). The Time Course of Task-Specific Memory Consolidation Effects in Resting State Networks. The Journal of Neuroscience, 34(11), 3982–3992.
ii) Liu, Y. Y., Slotine, J. J. & Barabasi, A. L. Controllability of complex networks. Nature 473, 167–173 (2011).
iii) Richard F. Betzel, Danielle S. Bassett Generative models for network neuroscience: prospects and promise J R Soc Interface. 2017 Nov; 14(136): 20170623
iv) Onorato, M., Vozella, L., Proment, D., & Lvov, Y. V. (2015). Route to thermalization in the α-Fermi–Pasta–Ulam system. Proceedings of the National Academy of Sciences, 112(14), 4208-4213.
v) Drazin, P. G., & Johnson, R. S. (1989). Solitons: an introduction (Vol. 2). Cambridge university press.

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