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Closing Date Tuesday, 2nd March 2021
Department Mathematical Sciences
Applications are open for a range of exciting projects around the theme of complex disease.
These 42-month PhD studentships, starting in October 2021, are offered through IMPACT – a doctoral training partnership between the Universities of Birmingham, Leicester and Nottingham. The University of Nottingham is advertising 8 projects in order to recruit to 4 studentships (2 IMPACT and 2 iCASE) in total.
You will study alongside other PhD students across a diverse range of projects, enabling you to think creatively and perform innovative, world-leading research. You will also benefit from the expertise of our research partner, the Research Complex at Harwell.
Applications will close at 5.00 pm on 7 January 2021. Funding is provided by the Medical Research Council. Please ensure that your application is submitted with all required documentation as incomplete applications will not be considered.
Full information about the eligibility criteria and application process are on the MRC IMPACT DTP website.
The following IMPACT project is available in the School of Mathematical Sciences:
Epilepsy as a dynamic disease - Professor Stephen Coombes
Are you looking to put your advanced skillsets in mathematics and computation to use in an interdisciplinary healthcare setting and help develop the next generation of tools for the clinical management and treatment of epilepsy? Do you want to work hand in hand with academics and a technology company working at the cutting edge of applying mathematical and computational methodologies to biomedical challenges? Then read on!
This project will build on a mathematical neuronal population activity model, recently developed at Nottingham (using a mixture of statistical physics and nonlinear dynamics), and extend this to include physiologically important components for the diffusion of ions in the extracellular space, and the resulting effect on electrical communication within cortical tissue. This is vitally important for the mechanistic interpretation of clinical EEG signals, against which the model will be validated, and will draw down from world leading biomedical expertise at Birmingham. Tools from machine learning will be juxtaposed with the mechanistic model to create a whitebox for predicting future brain states of individual patients using new observational data. This will further be augmented with routines for the prediction of critical transitions, giving the ability to avert or manage disastrous consequences of downstream seizures.
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