Job Title: Research Associate in Translational Neuroimaging
Project Title: VPH-DARE@IT: Virtual Physiological Human – Dementia Research Enabled by IT
Department: Medical Physics and Biomedical Engineering
Subsection: Translational Imaging Group, Centre for Medical Image Computing
Responsible to: Prof. Jem Hebden
Salary: Grade 7 £33,3535 - £40,313 per annum (this post is available for 24 months in the first instance)
This is an exciting opportunity for an enthusiastic researcher with knowledge in medical image processing and clinical research to join an internationally leading university research group. The aim of the project is to perform high throughput analysis across many large dementia cohorts, in order to better characterise the disease process and improve clinical decisions through support platforms.
The main purpose of this post is to perform large scale image biomarker extraction on thousands of samples pooled across some of the most important cohorts collected in dementia. This work is part of a large consortium created through a European FP7 grant entitled “Virtual Physiological Human – Dementia Research enabled by IT (VPH-DARE@IT”). The main goal of this consortium is to provide a multi-scale modelling approach to Alzheimer’s disease and other dementias, among other things allowing better understanding of the impact of environmental and lifestyle factors on the disease. The successful applicant will work with colleagues at the Translational Imaging Group, which is part of the UCL Centre for Medical Image Computing, in the creation or improvement of novel imaging biomarker pipelines and their implementation into the Nipype framework (http://nipy.org/nipype). They will also work with partners across Europe in the VPH-DARE consortium to integrate, validate, and extract these imaging biomarkers across thousands of subjects through the VPH-DARE research platform. Typical tasks could include, for example, managing the embedding of internal or external software within the host department environment, statistical analysis of large data results or maintain documentation of the framework for use by end users.
The successful candidate will have a good postgraduate degree or equivalent in Computer Science, Engineering, Physics, Mathematics or a related subject and be able to demonstrate good software engineering skills. They will also have demonstrated experience in clinical research and statistical analysis.
If you have any scientific queries please contact Dr. Marc Modat at email@example.com
How to apply: To apply and view a job description and person specification can be accessed via this link.