|Funding for:||UK Students, EU Students|
|Funding amount:||Not Specified|
|Placed On:||20th May 2019|
|Closes:||30th June 2019|
Project title: Applications and Implications of Machine Learning: Understanding and Predicting Healthcare Resource Usage and Patient Risk for Improved Population Engagement
Department/School: Informatics Research Centre/Henley Business School
Supervisors: Dr Weizi (Vicky) Li, Prof Keiichi Nakata and Prof Anupam Nanda
The gap between supply and demand in healthcare resources driven by an aging population has become an evolving challenge in the UK and global economy. This PhD studentship will investigate how artificial intelligence (AI) methods can provide insight into health resource usage patterns, predict patient risk and facilitate healthcare management. Existing AI methods applied in Electronic Health Records (EHR) will be investigated, and specific AI-based approaches for healthcare management and patient risk both within and outside the hospital will be developed.
This project is a partnership between the University of Reading and the Royal Berkshire NHS Foundation Trust (RBH), offered via the South East Network for Social Sciences (SeNSS) Doctoral Training Partnership, which is funded by the Economic and Social Research Council (ESRC). Several machine learning applications have already been successfully developed and come into operation for decision support in the hospital under the collaboration between Informatics Research Centre and Royal Berkshire Hospital.
How to apply:
Candidates are expected to submit their application to both the University of Reading and SeNSS
*Important notes*: Please quote the reference ‘GS19-040’ in the ‘Scholarships applied for’ box which appears within the Funding Section of your on-line application.
When you are prompted to upload a research proposal, please omit this step as the proposal content is included in SeNSS application below.
Application Deadline: 23:59 30th June 2019
Interview date: 9th July 2019.
Please note that, where a candidate is successful in being awarded funding, this will be confirmed via a formal SeNSS studentship award letter, which will be provided separately from Reading’s Offer of Admission.
For further details about this project please contact Dr Weizi Li (Weizi.email@example.com )
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