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Lecturer in Ophthalmic Data Science


Location: Centre for Public Health, School of Medicine, Dentistry & Biomedical Sciences, Belfast, BT12 6BA

Recruiter name: Queen's University Belfast

Role: Lecturer/Academic

Employer type: Academia

Contract type: Permanent

Hours: Full-time

Salary: £41,526 - £51,034 per annum

Recruiter type: Direct employer

Closing date:

We have received funding from the Belfast Association for the Blind to recruit a Lecturer in Ophthalmic Data Science who will drive research into patient phenotyping and clinical outcomes using Artificial Intelligence (AI) and data science.

Apply for this position

Ophthalmology has been revolutionised by automated technologies for measuring the structure and function of the eye in unprecedented detail. The Ophthalmology Research Group at Queen’s has been at the forefront of work undertaken in clinical trials and includes academic leaders who hold a distinctive and important position in national and international eye-research. We have received funding from the Belfast Association for the Blind to recruit a Lecturer in Ophthalmic Data Science who will drive research into patient phenotyping and clinical outcomes using Artificial Intelligence (AI) and data science. The post links directly with the work being undertaken as part of the Belfast Region City Deal and the HDR-UK Data Science initiatives.

The successful candidate will undertake research in the analysis of large medical and epidemiological datasets in the area of Ophthalmology / Vision Science, and will assist in statistical aspects of the research activities of the Centre for Public Health and the Wellcome-Wolfson Institute for Experimental Medicine in the School of Medicine, Dentistry & Biomedical Sciences.

The Lecturer will develop the research activities of the School by sustaining a personal research programme in ophthalmic data science through the analysis of large multi-dimensional data sets (including Electronic Care Records, epidemiological, imaging and / or multi-omics data), using both statistical and modern Machine Learning approaches. The Lecturer will also teach at undergraduate and postgraduate levels and contribute to School administration/outreach activity.

The successful candidate must have:

• Primary or higher degree in mathematics, statistics or a cognate subject
• PhD in a biomedical science, biology, epidemiology or a related discipline in which there has been a substantial data and statistics component
• A minimum of three years recent experience, at postdoctoral level, of the application of statistical and Machine Learning approaches to the analysis of health/healthcare or biomedical data and, in particular, experience of Ophthalmic Data Science
• Experience in performing statistical analysis using relevant statistical packages such as SPSS, STATA, SAS or the R software environment
• Recent experience of working collaboratively with people from cognate medical or biomedical research areas related to vision science/Ophthalmology

Informal enquiries may be directed to Prof Tunde Peto via email to [email protected]

The School of Medicine, Dentistry and Biomedical Sciences is part of the Faculty of Medicine, Health and Life Sciences. The School has the perfect balance of world-class teaching resources and internationally recognised research infrastructure and comprises of three education and three research centres.

The Centre for Public (CPH) Health is one of three research Centres in the School and is based within three buildings on the Royal Victoria Hospital site. CPH is committed to identifying the epidemiological and genetic risk factors that are important for the health of the individual and of the population and developing screening and interventions to reduce the burden of chronic diseases in the future, thus advancing the health of the public at a regional, national and international level, by increasing knowledge and influencing clinical and public health practice and policy.

Further information about the School and Centre can be found at

Queen’s University Belfast is a driver of innovation and talent based on excellence. Throughout the University, our academics collaborate across disciplines and with outside agencies and institutions on projects of world significance. We are connected and networked with strategic partnerships across the world, helping us to expand our impact on wider society locally, nationally and globally. The University is committed to attracting, retaining and developing the best global talent within an environment that enables them to realise their full potential.

We are a leader in gender equality and diversity, and are one of the UK’s most successful universities in the Athena SWAN initiative which promotes gender equality and career progression. The University and the School of Medicine, Dentistry and Biomedical Sciences hold an Athena SWAN Silver award in recognition of our commitment and success in addressing gender equality, representation, progression and success for all our staff.

We are ranked 1st in the UK for Knowledge Transfer Partnerships (Innovate UK), 9th in the UK for University facilities (Times Higher Education Student Experience Survey 2018) and 14th in the UK for research quality (Times and Sunday Times Good University Guide 2019).

Based in Belfast, a modern capital city, our beautiful campus is surrounded by abundant acres of parkland and is renowned as one of the safest and most affordable cities in the UK. There is an excellent range of local Schools from pre-nursery upwards and we are immensely proud of what our city and our University will offer you.

For full job details and essential/desirable criteria please refer to the candidate information link on our website by clicking apply. You must clearly demonstrate how you meet the criteria when you submit your application. For further information or assistance contact Resourcing Team via email on [email protected]

The University is committed to equality of opportunity and to selection on merit. We welcome applications from all sections of society and particularly from people with a disability.