Computational algorithms to model the interplay between brain structure and function

This exciting PhD project will develop computational models and analysis techniques to explore how the main connections between brain regions shape the characteristics of brain activity, and how different kinds of pathological processes damaging the connections of the network result in changes in the brain activity.

The successful applicant will do research in a multidisciplinary project expanding the areas of network science and signal analysis, in collaboration with clinical and neuroscience collaborators and benefitting from rich, publicly available datasets. The interest in the analysis of big datasets and networks is booming nowadays and this PhD provides an excellent opportunity to be trained in these areas.

We will develop novel models of network activity and signal analysis techniques able to unravel how the dynamical behaviour of brain activity depends on the diverse types of regions and dependencies on the brain. Building on recent developments in models of coupled oscillators and other computational approaches of brain activity, we will simulate physiologically realistic types of lesions and potential responses of brain activity.

The models considered in this PhD produce simplified but realistic brain activity and are well rooted in basic physics and network principles. As such, they are ideally suited to be exploited into computational algorithms for clinical application. However, their goodness of fit to brain activity is limited and more advanced approaches are needed to inspect complex behaviours in brain dynamics. The successful candidate will work to improve these models, accounting for advanced characteristics of the brain function and structure.

To do so, we will build on recent developments by our group and others. We expect that this PhD will lead to developments that could be transferred to the monitoring of disease in the clinic, and would also be potentially applicable to other fields.

Further Information: 

Closing Date: 

Wednesday, January 15, 2020

Principal Supervisor: 


Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.

Enthusiastic and self-motivated candidates are sought with, at least, an Honours degree at 2:1 or above (or International equivalent) in computer science, electronic engineering, mathematics, physics, or cognate disciplines. An MSc qualification will be advantageous but it is not an essential requirement.

The candidate is expected to have good programming and analytical skills.

Previous knowledge in areas related to complex systems (e.g., matrix algebra, networks, differential equations, etc.) or signal processing (e.g., Fourier, time series analysis) would be expected.


Further information and other funding options.

Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere