UE07: £35,333.00 - £42,155.00 Per Annum.
CMVM / MGPHS / USHER Institute.
Fixed Term available from 1 May 2023 to 30 April 2024 initially with possibility for extension subject to funding; Full time 35 hours per week.
The Centre for Medical Informatics at the Usher Institute within The University of Edinburgh is looking for a Research Fellow to conduct original research, focussing on the development, deployment, and evaluation of Computer Vision algorithms supporting the interpretation of medical images across several domains (chest CT scans, paper electrocardiograms, and retinal images). In particular, the post-holder will join the INPACT clinical study team (https://www.aidence.com/inpact/) and the SCONe project (https://www.ed.ac.uk/ophthalmology/scone) of clinical support tools in cardiovascular science using machine learning techniques for multimodal data integration and prediction of cardiac outcomes. The post-holder will work with Prof. Bernabeu at the Centre for Medical Informatics, Prof. Dhillon at the Centre for Clinical Brain Sciences and Dr Williams the Centre for Cardiovascular Science to produce material for publication and dissemination and to engage with project collaborators (including research visits, both national and international) and ensure delivery of a cutting-edge multidisciplinary programme of research.
The Opportunity:
The INPACT (Investigating Nodule Protocol Adherence using CADe/x Technology) study is a collaboration between Aidence, Hardian Health, and the University of Edinburgh, with funding from the UK’s National Health Service (NHS) through the AI in Health and Care Award. INPACT is a joint evaluation programme into the human-machine relationship. The aim is to get insights into the impact of an AI medical solution on radiology decision-making in lung cancer care. Most scientific literature on AI clinical applications focuses on their clinical validation, showing a device is safe, effective, and performs as intended. On the other side, clinical outcomes - the endpoints we are trying to influence by introducing AI devices in care pathways - are largely unexplored because AI technology is still in its early stages. INPACT is one of the few studies zooming in on the middle area: the real-world use of AI in clinical practice.
The Scottish Collaborative Optometry-Ophthalmology Network e-research (SCONe) is a pioneering project established in 2020 to build a world-leading, retinal image resource for innovation in eye research, healthcare, and education. In Scotland, community-based optometrists routinely collect millions of retinal images every year as part of eye examination appointments and many have been doing so for more than a decade. This represents a unique opportunity to create a large-scale longitudinal image resource that is representative of the primary care population. Within its initial two-year funded period, SCONe demonstrated the feasibility of bringing community-acquired retinal images for people aged 60+ together with other routinely collected healthcare data within the NHS National Safe Haven (NSH). In the next phase of the project, we are interested in leveraging this data for the development of algorithms for early detection of age-related macular degeneration and neurodegeneration.
Informal enquiries may be directed to Prof. Miguel O. Bernabeu, Professor of Computational Medicine ([email protected]).
Your skills and attributes for success:
- A postgraduate degree in a numerate subject including the use of statistical machine learning techniques in an application domain.
- The ability to use mainstream data science programming languages (such as R, Python, etc) for data extraction, transforming data, and statistical data analysis.
- A strong foundation on modern statistical machine learning methods including concepts such as convolutional neural networks and explainability/interpretability.
- A track record of publications in internationally leading journals and conferences.
- Experience working with multi-disciplinary teams, including clinical colleagues
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Please include your CV and a supporting statement with details of how you meet the knowledge, skills and experience required for this post.
As a valued member of our team you can expect:
An exciting, positive, creative, challenging and rewarding place to work. We give you support, nurture your talent and reward success. You will benefit from a competitive reward package and a wide range of staff benefits, which includes a generous holiday entitlement, a defined benefits pension scheme , staff discounts, family friendly initiatives , flexible working and much more. Access our staff benefits page for further information and use our reward calculator to find out the total value of pay and benefits provided.
The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. We are members of the Race Equality Charter and we are also Stonewall Scotland Diversity Champions, actively promoting LGBT equality.
If invited for interview you will be required to evidence your right to work in the UK. Further information is available on our right to work webpages.
The University is able to sponsor the employment of international workers in this role. If successful, an international applicant requiring sponsorship to work in the UK will need to satisfy the UK Home Office’s English Language requirements and apply for and secure a Skilled Worker Visa.
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