Research Fellow in Retinal Image Analysis

Full time: 35 hours per week

Fixed Term: contract for 1 year - available from 1^st January 2025 until 31^st December 2025

Location: Usher Building, Bioquarter, Edinburgh

The Centre of Medical Informatics at the Usher Institute within The University of Edinburgh is looking for an experienced data scientist to conduct original research as a key member of the British Heart Foundation (BHF) and Alan Turing Institute funded project “Uncovering retinal microvascular predictors of compromised brain haemodynamics in small vessel disease” aimed at discovering associations between the compromised brain haemodynamics observed in small vessel disease (SVD) and retinal vascular phenotypes derived from optical coherence tomography angiography (OCTA) images.

The Opportunity:

The successful candidate will be able to capitalise on data already acquired in two ongoing longitudinal studies on cerebral SVD and over a decade of experience in retinal image processing in Edinburgh. Co-PIs Wardlaw and Bernabeu are internationally recognised experts in SVD and cardiovascular mathematical modelling, respectively.

The successful candidate will conduct original research, centred around a) establishing a standard for OCTA image segmentation with particular emphasis on its robustness and applicability to routinely acquired data, b) developing novel metrics to characterise the structure and temporal evolution of microvascular networks based on the principles of Network Science and Machine Learning, c) investigating associations between OCTA-derived retinal microvascular phenotypes and compromised brain haemodynamics (cerebrovascular reactivity, cerebral blood flow, and blood brain barrier leak as well as cross-sectional and longitudinal lesion and diffusion tensor imaging changes).

Informal enquiries may be directed to Dr. Miguel O. Bernabeu (miguel.bernabeu@ed.ac.uk)

Your skills and attributes for success: 

• Possession of a PhD degree in a relevant discipline. 
• Demonstrable experience in computer programming, image processing, and machine learning. 
• Track record of published work. 
• Previous experience in biomedical image processing and/or experience in clinical studies is desirable.

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