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Echoes Around the Home.

Echoes Around The Home is a cross disciplinary project conceived and led by Dr Nicholas Firth (UCL Computer Science), working with social scientists Prof. Mary Pat Sullivan (Nipissing University Applied and Professional Studies) and Emma Harding (UCL Institute of Neurology), neuropsychologist Prof. Sebastian Crutch (UCL Institute of Neurology) and computer scientist Prof. Daniel Alexander (UCL Computer Science). This project has been funded by a Social Science Plus+ award from The Collaborative Social Science Domain UCL and will begin installing Echo’s in late March. More...

Publiziert: Feb 6, 2017 3:51:52 PM

Christos Talk

Dr. Christos Bergeles gave the honorary talk at the Greek Vitreoretinal Society Congress (http://gvrscongress.gr/en/) on 14th January 2017, titled "Advanced robotics for retinal micro-interventions and therapeutics delivery". The conference took place from 12th January 2017 to 14th January 2017, and several leading international ophthalmologists participated to discuss best clinical practices and new technological developments in vitreoretinal surgery. More...

Publiziert: Feb 2, 2017 4:08:30 PM

MICCAI Prize

Professor David Hawkes is the 2016 recipient of the MICCAI Enduring Impact Award.  The Enduring Impact Award Prize, founded in 2009,  is the MICCAI Society’s prestigious annual prize, awarded to a senior researcher whose work has made an enduring impact on the field of medical image computing and computer assisted interventions. More...

Publiziert: Nov 24, 2016 3:53:12 PM

Vacancies at CMIC

Research Associate in Disease Progression Modelling

UCL Department / Division

Medical Physics and Biomedical Engineering

Specific unit / Sub department

Translational Imaging Group (TIG)/Centre for Medical Imaging (CMIC)

Grade 7

Hours Full Time

Salary (inclusive of London allowance) £34,056 - £41,163 per annum

Duties and Responsibilities

Neurodegenerative processes such as Alzheimer’s disease or multiple sclerosis cover a broad range of distinct conditions. The accurate diagnosis and treatment of these pathologies requires the development of accurate computational models of the complex pathophysiology of neurodegenerative processes. 

To this purpose, the development of computational and statistical quantitative models of disease progression is currently a primary research focus of many academic and industrial actors. 

The project aims at combining statistical and image-processing techniques to model the pathological progression of neurological disorders in the brain of patients affected by neurodegenerative diseases. These models may combine several brain imaging modalities, and potentially investigate the complex interaction between brain changes and other clinical indices. Particular focus of the project will be in the modelling and simulation of clinically plausible evolution of biomarkers, represented by clinical and imaging data, by combining statistical/machine learning techniques with biomechanically/biophysically inspired dynamical models of brain changes. The candidate will rely on a number of methods developed within CMIC, and by the collaborators. The candidate will extend the current approaches in order to improve the modelling and prediction of neurodegeneration from clinical data, and to translate those discoveries into clinical practice. 

Due to the challenging setting of the project, characterised by large-dimensional data and relatively low sample sizes, as well as high data heterogeneity, the candidate will need to demonstrate sufficient expertise into the development of robust and reliable methods which can be translated into the clinic. Knowledge in statistics and optimization techniques is a fundamental requirement, as well as programming proficiency. 

This post is funded for 3 years in the first instance.

Key Requirements

The successful candidate will have a Honours Degree (2:1 or above) or equivalent in Mathematics, Engineering, Physics or Computer Science and/or a PhD in Computer Science, Machine Learning, Biomedical Engineering, Physics, Applied Mathematics or in a relevant related area. 

It is essential that applicants have experience in computer programming using C/C++, Python and Matlab. Experience in preparing statistical information, numerical optimization, be competent in medical image analysis and computer vision and have a demonstrable record of publications in peer-reviewed conference proceedings and scientific journals.

VIsit the UCL job page for more information and to apply.

Page last modified on 28 nov 16 15:35