A 4-year funded PhD studentship is available in the UCL Department of Medical Physics (Centre for Medical Image Computing [CMIC]) in collaboration with the Queen Square Multiple Sclerosis Centre at the UCL Queen Square Institute of Neurology. Funding will be at least the UCL minimum. Stipend details can be found here.
The successful candidate will join the UCL CDT in Intelligent, Integrated Imaging in Healthcare (i4health) cohort and benefit from the activities and events organised by the centre.
Project Background:
Multiple sclerosis (MS) is a disabling disease that causes disability in young persons costing the UK more than £3 billion per year. Images taken from brain and spinal cord can tell us what the current status of a patient is and how they may evolve. Current image processing tools to measure changes on brain and spinal cord are time consuming, require expensive and multi-step pipelines, and rely on the availability of high quality data which are often missing in the real world clinical practice. The candidate will develop a set of image processing tools using the latest advances in computer vision field to segment brain MRI scans, spinal cord MRI, and detect changes in these structures over time using data from both clinical trials and hospitals from across the UK. This project will use unique clinical trial datasets at the Queen Square Multiple Sclerosis Centre, MRI data from more than 8 hospitals from across the UK, and be able to test their potential for their applications in clinical trials in the industry with our collaborator (IXICO). This is a unique opportunity in between the academia and industry to develop the next generation of AI algorithms to impact drug development and patient care.
Research aims:
- Develop deep-learning based image simulators to enable efficient and semi-supervised image processing for the brain and spinal cord MRI (year 1 and year2)
- Develop ultra-efficient image segmentation models for detecting disease activity and disease progression in multiple sclerosis using longitudinal image processing (year 2 and year 3)
- Validate the developed models in clinical trials and real world data from our partner hospital (UCLH Trust / National Hospital for Neurology and Neurosurgery) and collaborating hospitals from across the UK
Person specification & requirements:
Qualifications, experience and knowledge
- BSc, MSc, or MD degree in a relevant technical or medical discipline
- Experience of working with PyTorch and computer vision libraries
- Knowledge of presenting or preparing scientific manuscripts in journals of conferences
Skills and abilities
- Programming skills in Python and specifically in PyTorch
- IT proficiency at advanced user level (Spreadsheet, Word Processing, Database, Email, Web based applications)
- Excellent oral and written communication skills
- Strong problem-solving abilities
- Good interpersonal skills with an ability to work co-operatively in a multidisciplinary setting
Personal attributes
- Resourceful and able to act on own initiative
- Interested in research and a commitment to supporting high quality research
Application Deadline: 31 May 2023
How to apply:
- Send an expression of interest and current CV to [Email Address Removed], [Email Address Removed] and [Email Address Removed]. Please quote Project Code:23022 in the email subject line.
- Make a formal application to via the UCL application portal. Please select the programme code Medical Imaging TMRMEISING01 and enter Project Code 23022 under ‘Name of Award 1'
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