What this PhD programme offers
HDR UK is funding six PhDs with leading UK universities and research organisations. This brand new programme offers the chance to carry out a doctoral research project at the leading edge of health data science.
Each project has been selected for its scientific excellence, importance and originality and will help deliver the aims and objectives of HDR UK’s Big Data for Complex Diseases (BDCD) Driver Programme.
Graduates will be well placed for a career at the forefront of health data research.
The research projects
- Characterising a high-risk Type 2 Diabetes phenotype using big data – the role of comorbidity and ethnicity: University of Bristol
- Advancing primary prevention strategies for complex diseases: University of Cambridge
- Expediting the diagnosis of cancer and other diseases where early diagnosis can improve clinical outcomes in patients presenting to a GP with new symptoms: UCL
- Repurposing and enriching cardiovascular risk prediction model to identify people at risk of cancer: UCL
- BLOod Test Trend for cancEr Detection (BLOTTED): an observational and prediction model development study using English primary care electronic health records data: University of Oxford
- Modelling the impact of diagnostic pathways in cancer and cardiovascular disease: University of Swansea.
See below for details of each project and to apply.
Who the PhD projects are for
The programme is for enthusiastic, talented students who want to use data-driven research to develop and shape the UK’s response to the most complex health challenges of our times.
- For eligibility details see the information about each PhD project.
- HDR UK is committed to promoting equality and inclusion, click here to find out more.
- We aim to accommodate specific needs and personal circumstances. Please make us aware of individual circumstances when applying or contact us directly at firstname.lastname@example.org. Please note the HDR UK PhD Student Privacy Notice.
If you have questions or require adjustments to the application process, please contact email@example.com.
Outcomes and benefits
This is a chance to earn a PhD from a leading university and by conducting a research project that will make a direct contribution to improving the health and care of patients.
Three or four years of funding will be available from HDR UK depending on the project. A three-year research project will be carried out at your home university and will be linked to HDR UK Big Data for Complex Disease Driver Programme aims and objectives.
Students will receive excellent training and career development opportunities in an environment that nurtures team science.
They can be hosted by a single research organisation or part of the studentship can be hosted by a second research organisation.
Each BDCD studentship award will comprise a three-year stipend and research costs of maximum £75,000 per studentship awarded to the host organisation(s). This is based on UK Research and Innovation (UKRI) minimum rate (Appendix B).
- Tax-free stipends with annual increases based on UKRI advertised rates
- Fully-paid tuition fees (and college fees where required) – international fee waivers are not available.
- Research costs of up to £5,000 a year
- Expenses and travel costs for conferences and events £300 a year.
Applications are open until 14:00 on 15 June 2023. Application forms are available underneath the information about each of the projects.
The provisional timeline is for interviews to take place w/c 19 June with offers being made w/c 26 June onwards. Studentships will generally begin in October 2023 or January 2024.
BDCD Driver Programme aims and objectives
For a wide range of complex diseases, deriving intelligence from nationwide, multisource, linked health relevant data has the potential to yield crucial insights that accelerate and enhance opportunities for innovation in disease detection, diagnosis, treatment, improved care, better outcomes and more rational health policy.
Cancer and cardiovascular diseases (CVD) are the two commonest causes of morbidity and mortality in the UK and globally, with incidence, morbidity and mortality increasing over the last several decades as the world’s population has aged.
Slowing these global trends requires approaches that recognise and exploit the power of whole, large population-scale health relevant data to catalyse health data science and its translation.
We also need to break down traditionally siloed disease and expertise specific domains, rising to the challenge of jointly addressing cancer, CVD, other complex diseases, their inter-relationships and their sequelae.
Crucially, we need to use the intelligence gained to translate into real benefit for citizens and patients and influence national and international policy and best practice.