We have funding from the National Institutes of Health (USA) together with partners from Cedars-Sinai Medical Center and University of California Los Angeles (California, USA), to investigate new non-invasive techniques of cardiovascular imaging with MRI.
We are looking for an enthusiastic and strongly motivated researcher to join us 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 (UoE) we collaborate with the Centre for Cardiovascular Science and the Clinical Research Imaging Centre at Queen's Medical Research Institute. The PI 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.
The culture of the School of Engineering and the University is open and diverse and we are committed to reflecting that in our appointment process.
Salary: £33,199 - £39,609 per annum
Closing Date: Friday 18th January 2019 at 5pm (GMT)
UoE Vacancy Ref:
Dr Sotirios Tsaftaris