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A 3-year PhD Studentship funded by Great Ormond Street Children’s Charity is available in the Population, Policy and Practice Research and Teaching Department, Great Ormond Street UCL Institute of Child Health. The studentship will commence in October 2022 under the supervision of Prof Neil Sebire.
Modern machine learning models provide powerful ways to analyse large-scale fixed and stationary datasets. They often outperform human-level ability in extracting patterns and creating predictive outcomes using large-scale data. However, these models fail to imitate humans' basic ability to continually learn in changing and non-stationary environments. The existing machine learning models are also often trained on a specific task and using single modality data.
The real world is, however, non-stationary. Healthcare records analysis requires continuous learning models that can analyse unseen data and adapt to the changes in the data (e.g. new treatments, new analysis, new experiences). Designing generalisable machine learning models that can analyse continuously changing electronic healthcare data requires new approaches to designing the learning methods. Continually learning models will provide novel ways to develop clinically applicable solutions to transform healthcare delivery by creating preventative and predictive measures. This will enhance patients' quality of treatment and care, reduce time, and improve the efficiency of clinical decision making.
The aim of this PhD research is to create an online digital consultation system with insights that could be extracted from large-scale electronic healthcare records. The research will initially focus on specific disease areas; however, the approach will be scalable across different conditions. By using standard ways of storing health data, it could also be used for children in multiple other centres across the country and beyond.
The PhD student will be based in Great Ormond Street Hospital Institute of Child Health at the University College London. The student will work at the GOSH DRIVE Unit (https://www.goshdrive.com/) within a team of Data Engineers and Data Scientists from the NHS, Academia, and Industry.
The student will receive a starting stipend of £17,796 per annum (including London weighting) as well as the cost of tuition fees based on UK fee status.
Personal Specification
Applicants should have a good first degree (UK 1st class or upper 2nd class honours degree or equivalent from abroad) and a Master’s degree (or equivalent work experience) in a relevant discipline by the time of registration.
Eligibility
This studentship covers the cost of tuition fees based on the UK (Home) rate. Non-UK students can apply but will have to personally fund the difference between the UK (Home) rate and the overseas rate where they are not eligible for UK fee status.
NB: You will be asked about your likely fee status at the interview so we would advise you to contact the UCL Graduate Admissions Office for advice should you be unsure whether or not you meet the eligibility criteria for Home fee status. Further information on Brexit and the definitions for fee status assessment can be found on the UCL website and also the UKCISA website (Higher Education: Definitions for fee status assessment).
Application
To apply, please send a current CV including the contact details of two professional referees as well as a cover letter to Drive.Research@gosh.nhs.uk. Enquiries regarding the post can be made to Prof Neil Sebire (neil.sebire@gosh.nhs.uk).
Deadline for receipt of applications: 3rd April 2022
Interview date: 19th April 2022