Wellcome Trust Featured PhD Programmes
University of Kent Featured PhD Programmes
Norwich Research Park Featured PhD Programmes
University College London Featured PhD Programmes
Cardiff University Featured PhD Programmes

SeNSS ESRC-funded Artificial Intelligence Studentship: Applications and Implications of Machine Learning: Understanding and Predicting Healthcare Resource Usage and Patient Risk for Improved Population Engagement

  • Full or part time
  • Application Deadline
    Sunday, November 18, 2018
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

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 behaviour and facilitate hospital operational management. Existing AI methods applied in Electronic Health Records (EHR) will be investigated, and specific AI-based approaches for hospital operational management and patient social behavior will be developed.

This project is a partnership between the University of Reading and the Royal Berkshire NHS Foundation Trust, offered via the Economic and Social Research Council (ESRC) and the South East Network for Social Sciences (SeNSS). Please click here (https://www.henley.ac.uk/school/business-informatics-systems-and-accounting/bisa-phd-programmes/esrc-artificial-intelligence-phd-studentship-fund-competition) to find a full project description.


We are seeking talented candidates with:
• a Master’s degree with distinction (or a 2:1 Bachelor Degree) in the areas of Artificial Intelligence, machine learning, data science, information management or health informatics
• experience in healthcare industry would be an advantage
• a track record of academic journal publication is desirable, or the ability to prepare high quality publications
• fluent English speaking (e.g. IELTS 7 or TOEFL 100 above)
• strong academic writing skills
• candidates should have an autonomous and proactive working style, good communication skills and the ability to work well in a team

How to apply:

1) Please submit an application for a PhD in Informatics and System Science via http://www.reading.ac.uk/graduateschool/prospectivestudents/gs-how-to-apply.aspx. Please quote the reference ‘GS18-173’ in the ‘Scholarships applied for’ box which appears within the Funding Section of your online application.
2) At the same time, please submit an application to SeNSS for funding for this studentship. Please contact Reading’s administrative lead, Dr Joanna John () for information on how to do this, and please discuss this application with Dr Li.
3) We would also like to see a sample of your written work. This might be a published conference or journal paper, or a chapter of your final year dissertation. Please include your writing sample with your SeNSS application form.

Application deadline:

23.59 GMT on 18 November 2018
Interviews will be held in the week commencing 10 December

Further Enquiries:

For informal enquiries, please email Dr Weizi Vicky Li (), Associate Professor of Informatics and Digital Health. For further information about SeNSS, contact Paul Newman, the SeNSS Co-ordinator ().

Funding Notes

• +3 or 1+3 award (length of award is dependent on the applicant’s past research methods training)
• Tuition fees, stipend (currently £14,777 p.a.) and access to additional funding for training
• Available full-time or part-time
• The studentship is open to UK, EU and international students.

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here
* required field
Send a copy to me for my own records.

Your enquiry has been emailed successfully

FindAPhD. Copyright 2005-2018
All rights reserved.

Let us know you agree to cookies

We use cookies to give you the best online experience. By continuing, we'll assume that you're happy to receive all cookies on this website. To read our privacy policy click here