tech4health: four year PhD in Digital Health Technologies

Apply and key information  

This project is funded by:

    • EPSRC

Summary

The challenges for healthcare systems are unprecedented, exacerbated by the burdens of infectious and chronic disease, ageing populations, inequalities, fragmented systems and workforce shortages. New technological approaches are needed to harness the potential of routine and novel health data and digital solutions to enable transformational improvement of care pathways and outcomes.

Our doctoral training programme will address this deficit by creating a new coordinated training curriculum, partnering world-leading academic and NHS organisations and industry, such that graduates can co-create and ideate, design, develop, evaluate and implement evidence-based digital health technologies.

This is a join centre between Ulster University (Ulster) and University College London (UCL) and this call relates to the Ulster intake. Early in year 1, students will have an individual skills assessment which will inform a personal training plan for the 4 years. In this first-year students will also conduct a combination of whole-cohort training as well as individual training and a 3-month secondment with industry. PhD projects will be selected and commence in month 9, continuing to the end of year 4, with ongoing training and engagement opportunities.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

  • Sound understanding of subject area as evidenced by a comprehensive research proposal
  • A comprehensive and articulate personal statement

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

  • Masters at 65%
  • Work experience relevant to the proposed project
  • Publications - peer-reviewed

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

  • EPSRC

The University offers the following levels of support:

Engineering and Physical Sciences Research Council (EPSRC)

Due consideration should be given to financing your studies. Further information on cost of living

Our fully funded PhD scholarships will cover tuition fees and provide a maintenance allowance  of £19,237 (tbc) per annum for three years* (subject to satisfactory academic performance).

These scholarships are open to applicants worldwide, regardless of residency or domicile.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Recommended reading

  1. https://www.england.nhs.uk/2019/06/nhs-aims-to-be-a-world-leader-in-ai-and-machine-learning-within-5-years/
  2. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/464088/BIS-15-543-genomics-in-the-UK.pdf
  3. https://www.iqvia.com/insights/the-iqvia-institute/reports-and-publications/reports/digital-health-trends-2021
  4. https://www.who.int/health-topics/health-workforce#tab=tab_1
  5. https://www.gov.uk/government/publications/medical-technology-strategy/medical-technology-strategy

The Doctoral College at Ulster University

Key dates

Submission deadline
Monday 24 February 2025
04:00PM

Interview Date
Mach 2025

Preferred student start date
15th September 2025

Applying

Apply Online  

Contact supervisor

Professor Dewar Finlay