Data Sciences and Brain Health across the Life Course session in 2020 SICSA Conference Oct 01, 2020 01:15 PM - 03:15 PM — Virtual Meeting (online)
Ophthalmic Medical Image Analysis MICCAI 2020 Workshop Oct 08, 2020 12:00 AM — Virtual Meeting (online)
Predictive Intelligence in Medicine MICCAI 2020 Workshop Oct 08, 2020 12:00 AM — Virtual Meeting (online)
PET is Wonderful Annual Meeting 2020 Oct 27, 2020 02:00 PM - 05:40 PM — Virtual Meeting (online)

eLearning

SINAPSE experts from around Scotland have developed ten online modules designed to explain medical imaging. They are freely available and are intended for non-specialists.


Edinburgh Imaging Academy at the University of Edinburgh offers the following online programmes through a virtual learning environment:

Neuroimaging for Research MSc/Dip/Cert

Imaging MSc/Dip/Cert

PET-MR Principles & Applications Cert

Applied Medical Image Analysis Cert

Online Short Courses

Vacancy: Postdoctoral Research Fellow in retinal image processing at University of Edinburgh

Postdoctoral Research Fellow post at University of Edinburgh in retinal image processing for the study of cerebral small vessel disease

The Centre for Medical Informatics at the Usher Institute within The University of Edinburgh seeks an experienced data scientist to conduct original research as a key member of the British Heart Foundation and Alan Turing Institute funded project "Uncovering retinal microvascular predictors of compromised brain haemodynamics in small vessel disease" aimed at discovering associations between the compromised brain haemodynamics observed in small vessel disease (SVD) and retinal vascular phenotypes derived from optical coherence tomography angiography (OCTA) images.

The successful candidate will be able to capitalise on data already acquired in two ongoing longitudinal studies on cerebral SVD and over a decade of experience in retinal image processing in Edinburgh.

The successful candidate will conduct original research, centred around a) establishing a standard for OCTA image segmentation with particular emphasis on its robustness and applicability to routinely acquired data, b) developing novel metrics to characterise the structure and temporal evolution of microvascular networks based on the principles of Network Science and Machine Learning, c) investigating associations between OCTA-derived retinal microvascular phenotypes and compromised brain haemodynamics (cerebrovascular reactivity, cerebral blood flow, and blood brain barrier leak as well as cross-sectional and longitudinal lesion and diffusion tensor imaging changes).

Enquiries can be directed to Dr Miguel O. Bernabeu at

For further information see https://www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.jobspec?p_id=050956

Closing date: 12 February 2020