Digital phenotyping in ophthalmology PhD Studentship

UCL Department / Division: UCL Institute of Ophthalmology
Duration of Studentship: Three years, available to start Autumn 2023
PhD Title: Digital phenotyping in ophthalmology
Supervisor(s): Professor Mariya Moosajee, Dr Peter Thomas, Dr Lee Jones and Dr Amy Strange from the Francis Crick Institute

We are offering a full-time, three-year PhD studentship to work with large datasets relating to eye/vision health and lifestyle to explore the potential of digital phenotyping in people living with sight loss. 

Digital phenotyping refers to the quantification of activity data collected from personal digital devices, such as smartphones. Smartphones are increasingly being used to collect health information, and monitoring these interactions can provide a detailed picture regarding a person’s overall health status. There is scope for this data to be linked with clinical measurements of the eye and vision to derive patterns and correlations to be tested and validated.

This project will involve working with an assortment of data types including images, functional assessments, and large streams of passive data collected via smartphones. The PhD will focus on developing statistical analysis models for digital phenotyping, including machine learning used for medical image analysis. You will provide statistical analysis plans for studies and undertake day to day planning of work. Similarly, you will be conducting detailed analysis of datasets, check validate and clean data.

The candidate will work with a diverse team of researchers based in Professor Mariya Moosajee’s Lab at the UCL Institute of Ophthalmology and at the Francis Crick Institute, London. There will also be opportunity to work with external collaborators in the field of data science.

Essential requirements
It is essential that you hold a degree or equivalent in life sciences, engineering, mathematics or computing. You will have excellent organisational and prioritisation skills, and good written and oral communication skills including ability to present complex information in a concise and clear manner to people from different backgrounds.

Duties and Responsibilities 
The successful candidate is expected to: 

• Conduct statistical analysis on existing datasets and have familiarity with statistical packages, such as R.
• Build and manage data pipelines to ensure data is processed and of a good quality ahead of analysis. Be able, with a team, to see clinical patients and collect usable patient images and data
• Work in collaboration with other researchers 
• Prepare progress reports 
• Prepare presentations 
• Travel for collaboration and other meetings or conferences 
• Prepare manuscripts for submission to international peer-reviewed journals 
• Contribute to the overall activities of the research team, department and be aware of UCL policies 

Person Specification 

• A good degree (2.1 or above; or equivalent EU/overseas degree) and/or MSc life sciences, engineering, mathematics or computating.
• Experience in coding using python, R and associated numerical packages for biomed analysis and of creating reproducible software using good practice such as version control
• Demonstrable interest in working with human subjects and the translational medicine field
• Experience in statistical modelling, epidemiology and / or healthcare data science. 
• Excellent methodological skills, particularly in project planning 
• High proficiency in written and spoken English is required 
• Very strong work ethic, with the ability to think creatively and work both individually and within a team

Desirable experience

• Experience of the command line and using high performance compute clusters
• Analysis experience with a range of data modalities including imaging, clinical and digital analytics
• Knowledge of Nextflow or other workflow tools for building complex data pipelines

Informal enquiries should be made to Dr Lee Jones and are encouraged (lee-jones@ucl.ac.uk). 

How to apply
Applicants should submit an application to the Research Degrees Manager ioo.pgr@ucl.ac.uk. You will be required to submit a CV, a covering letter outlining motivation, interest, and suitability for this project, and contact details for two academic referees. Please cite the PhD title of the scholarship you are applying for.

Enquiries relating to the application process should be sent to the Research Degrees Manager at ioo.pgr@ucl.ac.uk
Shortlisted candidates will be contacted directly for interview. 

The successful candidate is expected to start in Autumn term 2023, but flexibility with repect to the start date is possible.

Funding Notes
This studentship is funded for 3 years by the NIHR Biomedical Research Centre at Moorfields Eye Hospital and UCL Institute of Ophthalmology and includes UK UCL PhD tuition fees, laboratory costs and an annual salary stipend starting at £22,000 per annum.

Eligibility
The full studentship (tuition fees and salary stipend) is eligible to all UK nationals and some EU nationals depending on their settlement status. This scholarship will only cover UK home fees. 
Applicants who will incur international fees are welcome to apply but they must show that they can supplement the difference between UK and international fees in their application. (This fee difference is currently £26,240 per academic year). 

Application deadline: Monday 9 October 2023
Proposed interview date: TBC