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Mapping human brain development at new spatial resolutions using machine learning and 7T MRI Kings College London and University College London 4 years funding including fees*, training allowance and living costs (17k per year tax free). *EU applicants must meet the UKRI Residency Criteria to be eligible for full funding. We aim to bring together cutting edge advances in brain imaging and computer vision (that are also termed machine learning or artificial intelligence). MRI is the most important imaging modality for studying human brain development owing to its non-invasive nature and its flexibility to quantify different aspects of brain structure and function. Firstly, we want to use the sensitivity of new 7 Tesla MRI scanners to enable brain imaging at higher resolution. This is important because to image cortical development, the layered cortex (1.5-4mm thick) needs sub-millimetre sampling yet typical resolutions currently achieved (~1mm) are insufficient. Rapid developments in computer vision based on machine learning can enable computers to learn the mapping between high resolution and low resolution data, with pioneering work already performed in this area by the supervisory team. This will allow us to enhance existing low resolution scans once this mapping is understood, and further, use this enhanced data to improve our models of brain development. Person profile: We are looking for a highly motivated and committed person who is likely to have graduated from computer science, physics, maths or engineering. Graduates of other disciplines such as neurosciences are welcome to apply provided they are comfortable with highly computational work. You will be available to start by September 2019. Supervision: You will work in the team of Dr David Carmichael (primary) and Dr Jonathan O'Muircheartaigh within the KCL Biomedical Engineering and Imaging Sciences department based at St Thomas Hospital (opposite the houses of parliament) where you will have access to the London 7T imaging facility. You will also work closely with the team of Prof. Daniel Alexander (secondary) in the Computer Science department of UCL and can spend time flexibly in each centre. PhD Scheme: This LIDO (http://lido-dtp.ac.uk/) PhD provides a unique opportunity to work in a rich interdisciplinary environment at two internationally leading universities and departments that already work closely together on collaborative projects. Further details here https://www.findaphd.com/phds/project/mapping-human-brain-development-at-new-spatial-resolutions-using-machine-learning-and-7t-mri/?p109721<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.findaphd.com%2Fphds%2Fproject%2Fmapping-human-brain-development-at-new-spatial-resolutions-using-machine-learning-and-7t-mri%2F%3Fp109721&data=01%7C01%7Cdavid.carmichael%40kcl.ac.uk%7Cdc25dfe7079b496cc14f08d6dad8a29a%7C8370cf1416f34c16b83c724071654356%7C0&sdata=321kxs9Tzae0J%2B5sCIFag10RqPVXpb1uaJURchlojNo%3D&reserved=0> Please contact [log in to unmask]<mailto:[log in to unmask]> / [log in to unmask]<mailto:[log in to unmask]> David Carmichael Reader in Neuroimaging and Biophysics Honorary Reader, Radiology, Great Ormond Street Hospital NHS Foundation Trust Developmental Imaging and Biophysics Section Developmental Neurosciences Program UCL Institute of Child Health 30 Guilford Street London, UK WC1N 1EH Tel +44 (0) 2079052298<tel:%2B44%20%280%29%202079052298> Fax +44 (0) 2079052358<tel:%2B44%20%280%29%202079052358> http://www.action.org.uk/our_research/epilepsy_improving_brain_scanning_surgery https://iris.ucl.ac.uk/research/personal/index?upi=DWCAR66