MRI-derived network-based measures of white matter and grey matter as predictors of clinical outcomes and markers of treatment response in multiple sclerosis

The studentship is based in the Queen Square MS Centre, Russell Square House, 10-12 Russell Square, London, WC1B 5EH. This project is funded by a Progressive MS Alliance grant to develop ‘An MRI biomarker for disability progression for use in clinical trials’.

The aim of this PhD-studentship will be to help develop network-based methods to analyse clinical trial data in people with progressive MS. This work will be undertaken as part of an international collaboration, led by Prof. Douglas Arnold at McGill University, Canada, to establish a multidisciplinary collaborative network to develop next generation MRI markers of progression in MS.

In this sub-project we will develop MRI outcome measures that assess the integrity of brain networks using a variety of techniques. We will use a connectomics approach to measure white matter tract pathology and its effects on network performance. This has already shown considerable promise in relapse-onset MS, with network-based measures correlating substantially more closely with clinical scores than conventional whole brain white matter lesion volumes. In grey matter, we will extract cortical networks based on the covariance of thicknesses between regions). Covarying cortical regions will be identified in two ways, using a predefined automated anatomical labelling atlas and data-driven methods. We will then compare the relative performance of the white and grey matter network measures, and determine if they provide complementary information and can be combined into a single clinically-relevant structural network measure.

Main Duties
· To develop network-based methods to analyse clinical trial data in people with progressive MS.

· To liaise with other researchers collaborating on the project.

· To conduct leading-edge research, including writing original research articles for scientific journals and presentation at scientific conferences.

Key Requirements
• Honours degree (minimum 2:1) in a discipline related to this project;
• Experience in image analysis and statistical methods;
• Familiarity with a programming or scripting language (e.g., bash, MATLAB, R, or Python).


Person Specification
The person appointed will have the essential skills, abilities, personal attributes and experience listed below. In your application, you should demonstrate how you meet the person specification, using examples:

Honours degree (minimum 2:1) in a discipline related to this project (essential)
Experience in quantitative analysis of MRI scans
Working knowledge of Linux or Unix based systems
Practical experience with statistical analysis techniques and software.
Familiarity with at least one programming or scripting language (e.g., bash, MATLAB, R, or Python) (essential)
IT proficiency at advanced user level (use of commodity software such as word processors, email and spreadsheets) (essential)
Familiarity with neuroimaging (brain and spinal cord)
Experience of multiple sclerosis
Excellent oral and written communication skills (essential)
Good inter-personal skills with an ability to work co-operatively in a multidisciplinary setting (essential)
Resourceful and able to act on own initiative (essential)
Meticulous and accurate in all aspects of work (essential)
Strong problem solving abilities (essential)
Interested in research and a commitment to supporting high quality research (essential)

Informal enquiries
Please email Dr Declan Chard [Email Address Removed] or Prof. Olga Ciccarelli [Email Address Removed] for further information about the project.

Application procedures
Application is by CV and covering letter (including motivation for applying) emailed to Charlotte Burt [Email Address Removed]

Closing Date: 31st July 2018