Closing date: 12 May 2024

Key Information

Funding provider: Health Data Research (HDR) UK

Subject areas: Population Data Science

Project start date:

  • October 2024 (Enrolment open from mid-September)

Project supervisors:

  • Professor Rhiannon Owen (r.k.owen@swansea.ac.uk)
  • Dr James Rafferty
  • Professor Hamish Laing
  • Professor Keith Abrams (University of Warwick)

Aligned programme of study: PhD in Population and Health Data Science

Mode of study: Full-time

Project description:

Healthcare decision-making has previously focussed on developing recommendations for single conditions. However, standardised care for each chronic condition in isolation can be inappropriate for individuals living with multiple long-term conditions known as multimorbidity, and may lead to unnecessary polypharmacy. This PhD studentship aims to develop a modelling framework to estimate the natural history of disease in individuals living with multiple long-term conditions using population-scale, linked, electronic health records from the Secure Anonymised Information Linkage (SAIL) Databank Wales Multimorbidity e-Cohort (Lyons et al, 2021). This approach will allow estimation of the potential adverse effects (such as hospitalisations) of drug-on-drug interactions for the treatment of multiple conditions and associated genetic, environmental, or demographic risk factors. Further this PhD project will compare the efficacy of different combinations of treatments used in people with multiple long-term conditions, and assess potential health inequalities.   

Facilities 

The PhD student will be based in Population Data Science at Swansea University with visiting PhD Student Status at the Department of Statistics at the University of Warwick, benefiting from the stimulating and supportive environment and bespoke training programmes. The successful candidate will receive training to develop their knowledge and expertise in statistical modelling, epidemiology, population data science and health technology assessment, with the opportunity for their research to directly inform healthcare policy and practice. The successful student will have the opportunity to present their work at national and international conferences and workshops.  

This PhD is funded as part of the HDR UK Medicines in Acute and Chronic Care Driver Programme, which is a national collaboration that aims to understand and transform the use of medicines for patient benefit, and reduce medicines-associated harm. The Driver Programme has a particular focus on vulnerable populations including people living with multiple long-term conditions and those experiencing health inequalities. The successful candidate will be one of several PhD students contributing to the wider HDR UK Driver Programmes and will have the opportunity to collaborate with the wider HDR UK Driver Programme Team as well as access additional training and associated events hosted by HDR UK. 

Eligibility

Candidates must hold an Upper Second Class (2.1) honours degree. Candidates will need an MSc in Statistics/Biostatistics or Epidemiology/Health Data Science (with a strong analytical component) plus programming and data analysis skills/experience in R and/or Python. 

Experience of analysing large-scale linked electronic health record data and knowledge of Bayesian methods would be an advantage.

If you are eligible to apply for the scholarship but do not hold a UK degree, you can check our comparison entry requirements (see country specific qualifications). Please note that you may need to provide evidence of your English Language proficiency. 

This scholarship is open to candidates of any nationality.

If you have any questions regarding your academic or fee eligibility based on the above, please email pgrscholarships@swansea.ac.uk with the web-link to the scholarship(s) you are interested in. 

Funding

This scholarship covers the full cost of tuition fees and an annual stipend of £19,237.

Additional research expenses will also be available.

How to Apply

To apply, please complete your application online with the following information:

  1. Course choice – please select Population and Health Data Science / PhD / Full-time / 3 Year / October

    In the event you have already applied for the above programme previously, the application system may issue a warning notice and prevent application, in this event, please email pgrscholarships@swansea.ac.uk where staff will be happy to assist you in submitting your application.

  2. Start year – please select 2024
  3. Funding (page 8) –
  • ‘Are you funding your studies yourself?’ – please select No
  • ‘Name of Individual or organisation providing funds for study’ – please enter ‘RS600 - Health Technology Assessment'

*It is the responsibility of the applicant to list the above information accurately when applying, please note that applications received without the above information listed will not be considered for the scholarship award.

One application is required per individual Swansea University led research scholarship award; applications cannot be considered listing multiple Swansea University led research scholarship awards.

We encourage you to complete the following to support our commitment to providing an environment free of discrimination and celebrating diversity at Swansea University: 

As part of your online application, you MUST upload the following documents (please do not send these via e-mail). We strongly advise you to provide the listed supporting documents by the advertised application closing date. Please note that your application may not be considered without the documents listed:

  • CV
  • Degree certificates and transcripts (if you are currently studying for a degree, screenshots of your grades to date are sufficient)
  • A cover letter including a ‘Supplementary Personal Statement’ to explain why the position particularly matches your skills and experience and how you choose to develop the project.
  • Two references (academic or previous employer) on headed paper or using the Swansea University reference form. Please note that we are not able to accept references received citing private email accounts, e.g. Hotmail. Referees should cite their employment email address for verification of reference.
  • Evidence of meeting English Language requirement (if applicable).
  • Copy of UK resident visa (if applicable)
  • Confirmation of EDI form submission (optional)

Informal enquiries are welcome, please contact Professor Rhiannon Owen (r.k.owen@swansea.ac.uk).

*External Partner Application Data Sharing – Please note that as part of the scholarship application selection process, application data sharing may occur with external partners outside of the University, when joint/co- funding of a scholarship project is applicable.