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Precision Imaging is a world-leading centre for imaging with a mission to transform medical diagnosis and personalised health treatment. 

It brings together a wide variety of disciplines covering the Physics and computations aspects of Imaging Biomarkers and their application in Mental and Physical Health, and Biomedicine. At the heart it combines cutting edge-technology in imaging, big data analytics, and biophysical modelling to realise impact on complex diagnostic needs in precision medicine.

The PhD programme for the Beacon is now closed for the second intake scheduled for September 2019. Beacon studentships are fully funded three and half year PhD studentships on multi-disciplinary projects within the scope of the Beacon activities. Further details can be found below.

Students will be co-supervised by one or more academics from disciplines spanning the research activity of the Beacon.


To apply for a place on the programme, please consult the project list below and:

  • identify a project of interest and click on the project title
  • apply online via the University of Nottingham application page
  • for administration purposes please ensure that the lead school is initially flagged as the School of Mathematical Sciences (though any offer will come from the school of the supervisor)
  • in the personal statement section indicate that you are applying to the 'Beacon in Precision Medicine PhD programme' and make sure to include a ranked list of your preferred projects
  • upon submission send an email to Cheryl Ruse Head of Operations for the Beacon, your preferred project, and enclose a CV
  • Deadline for applications is 25 February 2019, with interviews for applicants to take place between 4 and 8 March 2019 

Applicants for the Precision Imaging PhD programme should have at least a 2:1 degree, or equivalent, in a project-relevant discipline. Funding is only available for UK and EU students.

For queries please contact  

PhD Projects
Project titleSupervisors    
Mathematical modelling and uncertainty quantification of distributed brain circuits to inform development of neuromodulation therapies

Daniele Avitabile, Peter Liddle, and Stephen Coombs

Precision computational modelling of magnetic resonance elastography to improve liver disease diagnosis  Matthew Hubbard, Deirdre McGrath, Reuben O’Dea, Bindi Brook, and Susan Francis 
Imaging-based neurophenotypes to model developmental mental health disorders Matteo Bastiani, Maddie Groom, and Chris Hollis 
Establishing autonomic and electrophysiological markers of arousal regulation and attention in children with ADHD

Maddie Groom, Lucy Cragg, Claudia Danielmeier, and Nic Blockley

ECLIPSE: Effect of carnitine on liver steatosis, insulin sensitivity, plasma glucose, skeletal muscle metabolism and energetics - a pilot study  Guru Aithal, Paul Greenhaff, Stephen Bawden, and Penny Gowland

Collaborator: Prarthana Thiagarajan 
Development of imaging-based stratification for haemorrhagic stroke trials Rob Dineen, Andrew French, and Niki Sprigg  
Deep phenotyping of Crohn's patients using a precision imaging approach to identify drivers and stratify risk of wasting and myosteatosis Gordon W. Moran, Paul Greenhaff, Penny Gowland, and Matthew Brook  
Developing multi-modal functional MRI approaches for clinical use Shahideh Safavi, Mike Barlow, Penny Gowland, Andrew Prayle, and Ian Hall
Evaluating the benefits and challenges of ultra-high field (11.7T) for magnetic resonance imaging and spectroscopy Richard Bowtell, Dorothee Auer, Penny Gowland, and Paul Glover
Quantification of novel MR imaging biomarkers in kidney disease

Sue Francis, Maarten Taal, and Nicholas Selby 

Looking like an expert: assisting automatic diagnosis using an AI attentional system Andrew French, Denis Schluppeck, and Rob Dineen 
Towards in vivoscoring tissue integrity in health and disease Galina Pavlovskaya, Ian Scott, and Richard Graham
Hyperpolarized MRI at ultra high magnetic field Thomas Meersman and Paul Glover  
Ultra-high resolution 7 Tesla fMRI, pushing the resolution to cortical layer Rosa Sanchez Panchuelo, Susan Francis, Xin Chen and Katrin Krumbholz

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