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Modelling casual effects of lifestyle and socio-economic factors on Type 2 Diabetes Mellitus using statistical machine learning

Project Description

Project description
It is known that the risk of developing Type 2 Diabetes Mellitus (T2DM) is increasing in the UK along with the rest of the World. It is believed that the culprits are lifestyle and environmental factors. However, it is less known which factors and their changes over time could drive trends in risk of T2DM. We aim to develop statistical machine learning models to study those causal links, and to model their impact on mortality and major adverse outcomes.

Specifically, the project will address the following research questions:
1) Can lifestyle behaviours and socio-economic factors, especially in early years, be identified as risk factors for developing T2DM in later life?
2) How changes in risk factors over time can influence trends in T2DM risks?
3) How do UK regions compare each other and against national average?

This is a three-year project from strategic research collaboration based at the new Liverpool Centre for Cardiovascular Science (LCCS) between Liverpool Heart & Chest Hospital, Liverpool John Moores University, Liverpool Health Partners, and the University of Liverpool for the advancement of cardiovascular and stroke research.

Supervisory team
The prospective PhD student will be supervised by Dr Ivan Olier, Professor Gregory Lip, and Professor Paulo J. Lisboa. Dr Olier is Senior Lecturer in Data Science. His research interests are in statistical and machine learning modelling of big data, with particular focus on modelling domains and relational data. He carries out data analysis over large and extensive primary care and cardiovascular datasets, and develops machine-learning methods around them for more complex analyses. Professor Lip, the LCCS leader, is an international research leader in atrial fibrillation (AF), a heart condition that causes an irregular and often abnormally fast heart rate, and leads to a high risk of stroke and death. Professor Lisboa is the head of the LJMU’s Department of Applied Mathematics and Engineering and Technology Research Institute. His research focus is in advanced data analysis for decision support.

The prospective PhD student

The successful candidate will work on statistical machine learning modelling and causal inferences of type 2 diabetes and associations with cardiovascular diseases, including complications, efficacy of treatments and clinical outcomes, using routinely collected national electronic health records.

Applicants should have a good first degree (2:1 or above) in a relevant discipline. A Master’s degree in Data Science or related discipline is desirable. The prospective PhD student will be based at Liverpool John Moores University. A programme of formal research training will be provided.

Funding Notes

Funding Notes
UK, EU and International students can apply for this studentship.
This is a self-funded opportunity with a requirement for the student or sponsor to cover the cost of full tuition and bench fees. Applicants should expect to commence study in January or September 2019.


For an informal discussion about this opportunity, please email Dr Ivan Olier ([email protected]) for more information.

Applicants should email a CV, covering letter detailing their suitability for the project and contact details of two referees to Dr Ivan Olier ([email protected] )

Applicants must be available for interview either face to face or via teleconference.

Please quote Reference APM1 in your application.

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