Scottish Radiological Society Spring Meeting 2021 May 14, 2021 09:00 AM - 05:00 PM — Virtual Meeting (online)
SINAPSE Virtual Happy Hour May 19, 2021 04:30 PM - 05:30 PM — Virtual Happy Hour (online)
9th Annual Scottish Radiotherapy Research Forum Jun 03, 2021 12:30 PM - 05:00 PM — Virtual Meeting (online)
Scottish Dementia Research Consortium Annual Conference 2021 Jun 16, 2021 10:00 AM - 03:30 PM — Virtual Meeting (online)
Medical Imaging Convention [rescheduled] Sep 15, 2021 - Sep 16, 2021 — National Exhibition Centre, Birmingham, England

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: Research Associate in Deep Learning and Medical Image Computing at Edinburgh

Research Associate in Deep Learning and Medical Image Computing at University of Edinburgh

We are looking for an enthusiastic and strongly motivated researcher to join us to investigate new non-invasive techniques of cardiovascular imaging with MRI, and build upon our efforts of bridging deep learning with medical image analysis. Areas of interest include: the design of segmentation and registration algorithms using machine learning techniques, and the development of algorithms for the extraction of biomarkers from cardiac MRI datasets available for this project.

The candidate will join an international team and will have the opportunity to participate in exciting projects where medical image computing helps us understand physiology and provide solutions that aid diagnosis. Beyond our international collaborations, within the UK and here at the University of Edinburgh we collaborate with the Centre for Cardiovascular Science and the Clinical Research Imaging Centre at Queen's Medical Research Institute. The PI, Dr Sotirios Tsaftaris, is also a fellow of the Alan Turing Institute, one of whose pillars is the use of machine learning for better health technologies.

Candidates should hold a PhD in electrical engineering, computer science or related discipline. A good record of international publications demonstrating prior experience in one or more of medical image analysis, machine learning, computer vision, image/signal processing is required. Experience in medical image analysis in MRI will be considered a plus. The candidate should have good programming skills, a strong mathematical background, good communication skills and the ability to work within a team.

This is a full time and fixed-term appointment for 12 months.

For further information see http://www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.jobspec?p_id=046047

Closing date: 18 January 2019