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Department of Computer Science

Geo-location as a Predictor of Type 1 Diabetes Blood Glucose

Primary supervisor

Additional supervisors

  • Paul Nutter

Additional information

Contact admissions office

Other projects with the same supervisor


  • Competition Funded Project (Students Worldwide)

This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Usually the project which receives the best applicant will be awarded the funding. Applications for this project are welcome from suitably qualified candidates worldwide. Funding may only be available to a limited set of nationalities and you should read the full department and project details for further information.

Project description

Help people with Type 1 Diabetes better manage their condition. Better management reduces clinical risks.

Type 1 diabetes is an autoimmune disease that causes the insulin-producing beta cells in the pancreas to be destroyed, preventing the body from being able to produce enough insulin to regulate blood glucose levels adequately. Insulin is an essential hormone that allows cells to utilise the carbohydrates/ sugar that has been consumed or produced by the liver. There is no known way to prevent type 1 diabetes. Treatment with insulin is required for survival, and is usually given by injection just under the skin but can also be delivered by an insulin pump.

When left untreated, or when poorly controlled, these raised blood sugar levels can cause both microvascular and macrovascular damage. This damage will eventually lead to deterioration in health and ultimately early death/ or disability. Essential to reducing these clinical risks is an understanding of how to accurately predict glucose concentration in the blood. This concentration is related to the food consumed and the efficiency of the body at metabolising this food. This is a wicked problem, and there is, likely, no perfect solution, we are 'simply' trying to get as close as possible. Instrumental is an understanding of food carbohydrates, glycemic index, glycemic load, and the bio-absorption of food both singularly and in combination. In this case, you will contribute to our broader Type 1 work by formulating studies, algorithms, and research prototypes to accurately predict blood glucose levels from the food we eat.

You will investigate how we might understand and predict hypoglycemia and hyperglycemia events using Geo-location and digital phenotyping without recourse to direct BG sensing. These models will typically be adaptive systems which enable personalised outcomes.

Person specification

For information


Applicants will be required to evidence the following skills and qualifications.

  • You must be capable of performing at a very high level.
  • You must have a self-driven interest in uncovering and solving unknown problems and be able to work hard and creatively without constant supervision.


Applicants will be required to evidence the following skills and qualifications.

  • You will have good time management.
  • You will possess determination (which is often more important than qualifications) although you'll need a good amount of both.


Applicants will be required to address the following.

  • Comment on your transcript/predicted degree marks, outlining both strong and weak points.
  • Discuss your final year Undergraduate project work - and if appropriate your MSc project work.
  • How well does your previous study prepare you for undertaking Postgraduate Research?
  • Why do you believe you are suitable for doing Postgraduate Research?