Supervision: Prof Seb Ourselin/Dr Andrew Melbourne/Prof Neil Marlow
The Translational Imaging Group (TIG) at University College London (UCL) is seeking to fill a doctoral position in medical image analysis. This PhD role will examine the neuroimaging and neuropsychological differences between extreme-preterm born and term-born adolescents and thus establish how the extreme-preterm neuroimaging phenotype relates to neurobehavioural function.
Birth at extremely low gestational ages is associated with complex effects on brain development that are life-long. There are few studies of the effects of extremely preterm birth extending into adolescence; one of the first is the UK MRC EPICure@19 study (www.epicure.ac.uk). This PhD will analyse the long-term appearance of extreme prematurity using Magnetic Resonance (MR) neuroimaging data and psychological outcome data from this cohort, born at 22-25 weeks of gestation, and now at 19 years of age. The on-going analysis will require the development of specialist tools that will be developed during this PhD and enable a comprehensively measurement of the adolescent neuroimaging phenotype of extreme prematurity; a phenotype that is currently unknown.
The neuroimaging protocol of the EPICure@19-years study comprises several state-of-the-art neuroimaging sequences including structural data for measuring the volumes of different brain regions and for inspecting the local tissue properties. Amongst these interesting tissue properties are the axon density and the myelin density. Additionally functional imaging data was acquired, for the assessment of how different regions of the brain are connected and for measuring the perfusion to the brain. Neuroimaging measurements will be supplemented with neuropsychological outcome data from task-based experiments relating to social processing, perception, mobility and IQ.
The differences that we expect to see in these imaging data are not yet known. This PhD will enable one of the first analyses of the appearance of the extreme-preterm brain at adolescence.
The applicant should have:
- A M.Sc. degree in computer science, engineering, biomedical engineering, physics, applied mathematics, or a related area.
- Strong programming skills.
- Strong mathematical and problem solving abilities.
- Strong motivation and enthusiasm towards research.
- Ideally, some experience with medical imaging data.
The studentship compromises of UK/EU fees level and a tax-free stipend of £16,851 per annum. In order to qualify candidates must be UK/EU passport holders or qualify for UCL home fees status. The start date for the position is 26th September 2016.
To apply please send the following to "> as soon as possible.
- A copy of your CV.
- Contact details of 2 academic references.
- A cover letter stating the reasons you are applying for this studentship.