Job Description

Position
We have funding from the National Institutes of Heath (USA) together with partners from Cedars-Sinai Medical Center, University of California Los Angeles (California, USA), and Siemens, 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 machine learning with medical image computing. 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.

Environment
The candidate will join a dynamic, 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. In addition, UoE is a member of the Alan Turing Institute, one of whose pillars is the use of machine learning for better health technologies.

Requirements
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.

The position is full time and fixed term for 12 months.
The post is available immediately.

Salary: £31,656 - £37,768 per annum

Closing Date: Friday 6th May 2016 at 5pm (GMT)

How to apply
To apply you must submit a formal application as indicated here (please address how you fit some of the criteria within the relevant sections and within a potential cover letter):
https://www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.jobspec?p_id=035982

Informal inquiries:
You are encouraged to contact Dr Sotirios A Tsaftaris (email: s.tsaftaris@ed.ac.uk) for additional information on the position, preferrably after you have formally applied.

Additional information about the PI (Dr Tsaftaris):
http://tsaftaris.com

Follow @eurasip