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