Advanced analytics to investigate novel BP wearable technology to improve cardiovascular outcomes and falls

There are multiple opportunities using these data sets for PhD study to develop and apply novel methodologies including: 

• Use of prognosis research methods to investigate which summary measure of 24-hour Blood pressure profiles is predictive of falls, major adverse cardiovascular events, or all-cause mortality, over and above existing prediction tools.
• Use of machine learning techniques to investigate whether patterns of BP profile, may have superior predictive value over summary measures currently available.
• Use of propensity score matching to address confounding to undertake a causal inference study asking whether treatment change on basis of 24-hour BP recording changes outcomes.
• Use of individual patient data meta-analysis to combine data from three cohorts in a 2 stage IPD meta-analysis process.

This PhD will form part of a larger programme of research funded by the NIHR which aims to improve the safety of BP treatment in older adults at risk of falls and make it easier for patients to be involved in decisions about their treatment. The databases used in this PhD will be the largest and most detailed of their kind worldwide and help us to better understand hypertension in old age. 

The candidate would be embedded in a vibrant group of data scientists and clinicians working on a range of projects harnessing routine health and care datasets. This would enable a range of training opportunities and apprenticeship learning opportunities as well embed the candidate in inter-disciplinary networks which may foster future opportunities for collaboration and career development. This work would be undertaken in collaboration with leading centres in hypertension research at the University of Oxford, falls research at Trinity College Dublin, and ageing research at Harvard University.

We are seeking an exceptional candidate to become a future leader in health data science, providing access to training activities through the Centre for Data Science and Ageing. The successful candidate will join a vibrant cohort of PhD students, funded by the Health Data Research UK and the Dunhill Medical Trust Reimagine Ageing Doctoral Research Fellowship programmes, fostering interdisciplinary collaboration and networking across the UK.

This PhD

This PhD presents an opportunity for a motivated candidate from medical statistics/ data science/ mathematics background to use routine health care data to develop skills that include but are not limited to: 

• data management and linkage
• writing code to clean, link and identify different continuous and categorical variables in routine data,
• epidemiological analysis including survival analysis adjusting for competing risks and addressing missing data,
• using advanced methods to deal with confounding such as propensity score matching,
• undertaking causal inference using routine data, and
• combining data for analysis from different data sets using individual patient data meta-analysis techniques.

A number of different software will be available for cleaning, describing and analysing the data including Python, R, SQL and STATA.

Other Conditions

• Applicants must not have already been awarded or be currently studying for a doctoral degree.
• Awards must be taken up by January 2025
• Applicants must live within a reasonable distance of the University of Leeds whilst in receipt of this scholarship.

To apply for this scholarship opportunity applicants should complete an online application form and attach the following documentation to support their application. 

• A full academic CV
• Degree certificate and transcripts of marks
• Evidence that you meet the University’s minimum English language requirements (if applicable)

To help us identify that you are applying for this scholarship project please ensure you provide the following information on your application form;

• Select PhD in Medicine as your programme of study
• Give the full project title and name the supervisors listed in this advert
• For source of funding please state you are applying for a LIHS PhD Scholarship

Applicants to research degree programmes should normally have at least a first class or an upper second class British Bachelors Honours degree (or international equivalent) in a relevant subject area. A Master’s degree is desirable, but not essential.

The minimum English language entry requirement for research postgraduate research study in the School of Medicine is an IELTS of 6.5 overall with at least 6.0 in each component (reading, writing, listening and speaking) or equivalent. The test must be dated within two years of the start date of the course in order to be valid.

For further information about the application process please contact the Admissions team e: fmhpgradmissions@leeds.ac.uk

For informal enquiries regarding this project please contact Dr Oliver Todd: O.Todd@Leeds.ac.uk