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Data Scientist

The University of Edinburgh - College of Medicine and Veterinary Medicine, School of Clinical Sciences, Centre for Clinical Brain Sciences

Location: Edinburgh
Salary: £37,099 to £44,263
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 11th December 2023
Closes: 4th January 2024
Job Ref: 9064

Full time 35 hours per week

Fixed term 24 months

1 post

We are looking for a highly motivated person to take on an exciting project opportunity and be the driver for an Innovate UK funded Knowledge Transfer Partnership (KTP) between the University of Edinburgh and Optos. The project aims to revolutionise the way in which damage to the retina, causing vision loss, is detected and managed by clinical eye-care specialists at a time when new treatments are being licenced for use, bringing hope of saving sight amongst sufferers. Optos' imaging devices provide a comprehensive scan of the retina, providing clinicians with high-quality images with which to detect damage in the retina. The key objective of this partnership is to take leading edge knowledge of retinal image processing and analysis, and prototype Machine Learning/Artificial Intelligence methods to automatically detect and quantify damage in the retina and translate that into software for devices that will be usable in the clinical environment. 

The Opportunity:

This post is advertised as full-time (35 hours per week) and will be a University of Edinburgh employee but embedded within Optos to build new technologies. It is funded through a KTP award, a UK Government flagship scheme intended to promote sustained and mutually beneficial relationships between universities and industry. There is a professional development budget available for the Associate as well as funded training courses on business and project management.

Your skills and attributes for success: 

  • Knowledge and experience in Artificial Intelligence (AI), Machine Learning (ML), image analysis, or data analysis.
  • Programming skills and an excellent understanding of AI and ML techniques
  • Ability to work effectively as part of a team
  • Experience in clinical research
  • Ability to communicate complex information clearly
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