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UPDATE: We are delighted to announce that EPSRC have funded our CDT for five more years under the new name EPSRC Centre for Doctoral Training in Intelligent Integrated Imaging in Healthcare (i4health).

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12 Jul

Identifying automated CT features predicting outcome in cystic fibrosis

Allocated Projects

A PhD studentship (4-year funding – MRes + Phd, with a tax free stipend of £16,851) sponsored by the Cystic Fibrosis Trust is available in the UCL Centre for Medical Image Computing

The successful candidate will join the UCL CDT in Medical Imaging cohort and benefit from the activities and events organised by the centre.

Cystic fibrosis is a genetically inherited condition that results in a mutation in a protein that regulates the flow of fluids and salt in and out of various cells in the body. Whilst this results in damage to several organs such as the pancreas and bowel, it is damage to the lungs that predominantly impacts a patients quality of life and most influences life expectancy.

Lung disease can be visualized on computed tomography (CT) imaging and provides an estimate of disease severity. However quantifying disease severity is currently only achieved using crude visual scores of airway damage and parenchymal features on a lobar level. Using such visual lobar scores reduces the ability to identify subtle change in a patients CT scan over time. For the purposes of a drug trial endpoint, more precise measures of disease worsening are necessary and computer analysis of CT imaging could provide the answer.

The current study proposal aims to develop quantitative tools to identify and measure the presence and severity of airway damage on CT imaging in patients with cystic fibrosis. As a secondary aim, we also plan to characterize textural features on CT imaging to allow the quantification of lung parenchymal damage. The primary study aim is to link imaging phenotypes to patient genotypes, and thereby develop a more personalized approach to disease stratification in cystic fibrosis.

The candidate is expected to have at least an upper second-class degree in physics, engineering or related area and a Masters degree or equivalent in a relevant subject area. A strong mathematics background is essential. Good working knowledge of C++ and/or Python or MATLAB is preferable. The candidate must be committed to deliver excellence in research, and will also be expected to provide regular, biannual reports on research progress and present at international conferences.

As the post is funded via the EPSRC, applications are restricted to candidates from the UK or EU, though EU candidates must have been living and/or working in the UK for 3 years prior to the application date.

To make an application please send a CV and contact details, including email addresses for two referees, to Dr Joseph Jacob at Please include a covering letter indicating why you believe you are suitable for the studentship, your long-term research and professional goals, and any particular expertise you have that you feel may be applicable in this work.

Closing date: 30th of July 2018, with start date of September 24th 2018.