Visualising Risk in Elder Care

  • Phd
  • Fees + annual stipend
  • 3 May 2017

A recent research highlighted the potential for communicating about care risks through visual means rather than only words or numbers to convey likelihood or seriousness of possible harm. Analysis of a situation and prediction of the level of associated harm is conducted by humans who assess the situation by gathering information and relating this to experience, research and theory to make a judgement. However the relevant research data is very diverse, and difficult to access. Computational intelligence seeks to develop models that can reason, understand or learn like a human. The ability to spot patterns, adapt to new and unusual data, account for uncertainty, and to be robust to non-perfect and incomplete data are hallmarks of computational intelligence methods. This project aims to introduce computational intelligence approaches to data analysis, to predict an associate harm level and hence provide decision support for the health and social care professional in communicating about risk.


Candidates should have ordinary UK residence to be eligible for both fees and maintenance. Non UK residents who hold ordinary EU residence may also apply but if successful will receive fees only. All applicants should hold a first or upper second class honours degree in computer science or psychology or a cognate area. The role will require knowledge and skills in quantitative data analysis and computer programming, and an interest in health and social care services. Applications will be considered on a competitive basis with regard to the candidate’s qualifications, skills experience and interests.


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Fees and annual stipend of £14,553 - awarded for a period of up to three years subject to satisfactory progress.
Successful candidates will enrol as of 1 October 2017, on a fulltime programme of research studies leading to the award of the degree of Doctor of Philosophy

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