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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 open, with a first intake scheduled for September 2018. Currently available are fully funded three 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 up to three projects 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, confirming your three preferred choices, and enclose a CV
  • Deadline for applications is 16/03/2018, with interviews for applicants to take place between 26/03/2018 and 29/03/2018.

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    
Cross-modal integration for modelling the brain connectome

Stam Sotiropoulos
Theo Kypraios

Precision computational modelling of Magnetic Resonance Elastography to improve liver disease diagnosis  Matthew Hubbard
Deirdre McGrath 
Reuben O’Dea 
Bindi Brook 
Susan Francis 
Impact of the colon environment on drug absorption from modified release oral formulations  Luca Marciani
Martin Garnett 
P Gershkovich 
S Stolnik 
Robin Spiller 
Mathematical modelling and uncertainty quantification of distributed brain circuits to inform development of neuromodulation therapies  Daniele Avitabile
Peter Liddle,
Stephen Coombes 
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 
Penny Gowland

Collaborator: Prarthana Thiagarajan 
Deeper understanding of CADx for MRI  Andrew French
Paul Morgan 
Michael Pound, Yorgos Tzimiropoulos. 
Ultra-high resolution 7 Tesla fMRI, pushing the resolution to cortical layers: implications for understanding brain plasticity  Susan Francis
Rosa Sanchez Panchuelo

Xin Chen
Katrin Krumbholz 
Combining brain imaging and brain stimulation to deliver novel therapies for brain health conditions Stephen Jackson Matthew Brookes 
Towards better and individualised characterisation of multiple sclerosis using deep learning  Xin Chen
Stam Sotiropoulos
Andrew French
Nikos Evangelou 
Novel cardiovascular MR in precision medicine – the cardiovascular response during acute bouts of exercise in health and disease Charlotte Bolton
Susan Francis
Paul Greenhaff 
Development of hyperpolarized 83Kr whole body MRI at SPMIC’s 7T facility  Thomas Meersmann Galina Pavlovskaya 
Paul Glover 
Developing a multi-modal MRI approach to precision medicine of lung disease  Penny Gowland
Ian Hall 
Mike Barlow
Andrew Prayle 


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