PET is Wonderful Annual Meeting 2020 Oct 27, 2020 02:00 PM - 05:40 PM — Virtual Meeting (online)
Through the Looking Glass: Breaking Barriers in STEM Oct 28, 2020 12:00 PM - 03:30 PM — Virtual Meeting (online)
NRS Mental Health Network Annual Scientific Meeting 2020 Nov 04, 2020 09:00 AM - 05:30 PM — Virtual Meeting (online)
Scottish Radiological Society Annual General Meeting 2020 Nov 06, 2020 09:30 AM - 03:30 PM — Virtual Meeting (online)


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: Research Fellow in MRI perivascular spaces image analysis at University of Edinburgh

Postdoctoral Research Fellow position in Edinburgh on project using computational methods to measure perivascular spaces on brain MRI in patients at risk of neurodegenerative diseases

The Centre for Research into Ageing and the Brain at the Centre for Clinical Brain Sciences within The University of Edinburgh seeks an experienced post-doctoral medical image analyst to conduct original research as a key member of the recently funded international project "Perivascular spaces: an early marker of vascular contributions to neurodegeneration". Perivascular spaces (PVS) have recently been identified on brain Magnetic Resonance Imaging (MRI), as marker of small vessel dysfunction and potential biomarker of future risk of neurodegeneration and dementia. The work will focus on testing and further refining recently developed computational methods to measure PVS on brain MRI in patients at risk of small vessel disease (SVD), dementia, and other neurodegenerative diseases. The successful candidate will conduct original research, centred around: a) testing and improving computational methods (inc. machine learning approaches) for measuring PVS on human brain MRI; and b) discovering associations between PVS morphologies, current and future cognitive outcomes, using data from many studies reflecting different patient groups.

The successful candidate will be hold a PhD degree in a relevant discipline, have demonstrable experience in MRI computational image analysis preferably in SVDs or dementia, statistical and database management experience, and a track record of published work. Previous experience in studies linking MRI findings with cognitive, functional and neurodegenerative disease outcomes would be advantageous.

Please contact Prof JM Wardlaw if you wish to discuss the post informally.

For further information see

Closing date: 1st May 2020