About the Project
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.
• Applicants should hold or expect to gain a Master’s degree or minimum of a 2:1 Bachelor Degree or equivalent in information management, health informatics, artificial Intelligence, data science, population health, health economics or other related areas.
• English requirement: minimum IELTS 6.5 or equivalent
• The studentship is open to UK, EU and international students.
How to apply:
Candidates are expected to submit their application to both the University of Reading and SeNSS
• University of Reading application: To apply for this studentship please submit an application for a PhD in Informatics and System Science at http://www.reading.ac.uk/graduateschool/prospectivestudents/gs-how-to-apply.aspx.
*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.
• SeNSS application: At the same time, please fill in forms to SeNSS for funding for this studentship. Please contact Reading’s administrative lead, Trica Burgess ([Email Address Removed] ) for the SeNSS application pack and information on how to do this.
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 ([Email Address Removed] )
Promotion through supervisor networks
• +3 or 1+3 years award (length of award is dependent on the applicant’s past research methods training)
• Funding covers full tuition fees plus UKRI stipend
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