Subsection: Translational Imaging Group (TIG) within the Centre for Medical Imaging Computing (CMIC)
Duration: 3 years
Stipend: £16,851 per annum tax-free, full fees paid.
Applications are invited for a PhD funding opportunity based within the Translational Imaging Group of the Centre for Medical Image Computing at UCL, and sponsored by Brainminer,ltd. and the EPSRC.
The Quantitative Neuroradiology Initiative (QNI), a joint venture between the Translational Imaging Group and the National Hospital for Neurology and Neurosurgery, aims to translate novel state-of-the-art imaging biomarkers to clinical practice, improving patient care. These machine learning algorithms and mathematical models have shown to produce clinically useful biomarkers under the assumption that the input imaging data is of sufficient quality, with no signal abnormalities. This project aims to use advanced machine learning techniques, namely deep learning, to detect problematic input images and signals containing imaging artifacts (e.g. patient movement during the scanning), poor acquisitions (e.g wrong sequence or parameters), and mislabeling (e.g. scanned the wrong body part). This analysis will not only provide a real time warning system for clinicians and radiographers, but also ensure that the data is problem-free for fully-automated image analysis.
1. Cover letter explaining why you feel suitable for this post and background.
3. Names and contact details of 2 academic or work referees
Stipend: £16,851 per annum tax-free, full fees paid. Exact amount TBC
In order to qualify candidates must be UK passport holder or have lived in the UK for at least 3 years.