09 Nov 17. Job - PhD vacancy (DTP)
Signal analysis of dynamic magnetic resonance image acquisitions for the study of subtle blood-brain-barrier changes in small vessel disease
PhD Vacancy – Doctoral Training Programme (DTP) in Precision Medicine
Project title: Signal analysis of dynamic magnetic resonance image acquisitions for the study of subtle blood-brain-barrier changes in small vessel disease
Supervisors: Dr. Maria del Carmen Valdés Hernández
There is evidence that subtle breakdown of the blood–brain barrier (BBB) is a pathophysiological component of several diseases, including cerebral small vessel disease and some dementias. Dynamic contrast-enhanced MRI (DCE-MRI) and tracer kinetic modelling is used to assess BBB leakage (Heye et al. 2014).
Our MRC funded Doctoral Training Programme (DTP) in Precision Medicine focuses on training PhD students in key MRC skills priorities in Quantitative Skills (mathematics, statistics, computation, developing digital excellence) as applied to variety of data sources (from ‘omics’ to health records) or Interdisciplinary Skills including imaging, and stratified medicine.
The vision of this programme is to support research training at the interfaces between biological, clinical, societal and computational systems. We want our cadre of Precision Medicine researchers to develop the adaptability needed to make them agile researchers in this fast moving area.
The programme has a tiered access model allowing students to undertake a 3.5 year PhD, for students who already have a Masters degree, or a 4 year PhD for those entering with a BSc Honours. The mandatory taught training element is a vital aspect of the programme and is designed to ensure students gain skills aligned with the MRC skills priorities outlined above Students on the 3.5 year programme are required to take 30 credits of study in Year 1, and those on the 4 year programme 120 credits across the first 3 years, with 80 credits completed in Year 1. Mandatory taught elements will include Statistics, Research Ethics, Innovation and Entrepreneurship, Health Economics, Data Management and Bioinformatics.
1) Recognise and identify the state-of-art and difficulties of modelling dynamic data from medical images in the study of subtle BBB permeability dysfunction
2) Identify and familiarise with the state-of-art signal processing methods used in biomedical signal analyses and translate them to medical images
3) Identify and familiarise with the existent image processing denoising methods and apply them to dynamic MRI acquisitions
4) Identify and apply the signal processing methods that can be useful in the analysis of DCE-MRI for the study of subtle BBB leakage
5) Evaluate the most promising signal processing methods for the signal decomposition and analysis of DCE-MRI applied to the study of subtle BBB leakage in regions of interest
6) Summarise the results of the evaluations made throughout and consolidate the software developments/approaches deemed to be more suitable.
7) Acquire skills in data management.
8) Familiarise with and apply clinical research regulations.
The successful candidate should hold an undergraduate or MSc degree in Electronic Engineering, Computer Science, Biomedical Sciences or a relevant subject, with particular interest or expertise in signal processing, biological image analysis, medical image computing, computer vision or machine learning.
If interested, the prospective student can apply via the link below.