Application Form
PhD Studentship in Healthcare Data Quality [PhD_HDQ_GSLHDB]

JobRef: 8863
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PhD Studentship in Healthcare Data Quality [PhD_HDQ_GSLHDB]

POSTED:April 12, 2021
LOCATION:Trinity College Dublin
CLOSES:July 9, 2021
Duration:4 Years
Reports to:Prof Gaye Stephens, Prof Lucy Hederman, Prof Damon Berry
Salary:€18,500 stipend per annum (non taxed) plus university fees
Closing Date:July 9, 2021
Anticipated start date: September 2021



  • Contribute to the ADAPT research agenda that pioneers and combines research in AI-driven technologies: Natural Language Processing, Video/Text/Image/Speech processing, digital engagement & HCI, semantic modeling, personalisation, privacy & data governance.
  • Work with our interdisciplinary team of leading experts from the complementary fields of, Social Sciences,  Communications, Commerce/Fintech, Ethics, Law,  Health, Environment and Sustainability.
  • Leverage our success.  ADAPT’s researchers have signed 43 collaborative research projects, 52 licence agreements and oversee 16 active commercialisation funds and 52 commercialisation awards.  ADAPT has won 40 competitive EU research projects and obtained €18.5 million in non-exchequer non-commercial funding. Additionally, six spinout companies have been formed. ADAPT’s researchers have produced over 1,500 journal and conference publications and nearly 100 PhD students have been trained.

As an ADAPT-funded PhD researcher you will have access to a network of 85 global experts and over 250 staff as well as a wide multi-disciplinary ecosystem across 8 leading Irish universities. We can influence and inform your work, share our networks and collaborate with you to increase your impact, and accelerate your career opportunities. Specifically we offer:

  • Opportunity to build your profile at international conferences and global events.
  • A solid career pathway through formalised training & development, expert one-on-one supervision and exposure to top specialists.
  • A Fully funded, 4 year PhD postgraduate studentship which includes  a stipend of (€18,500 per annum – non taxed), along with equipment, annual travel funding
  • Funding for annual student fees


It is estimated that over 2,000 exabytes of health data were created globally in 2020. Much of this data was generated to support care, in acute and primary care, in connected health and other contexts.  It is well known that modern AI techniques often require large training data sets.

This immense and rich global eHealth information resource, when it is suitably organised and semantically linked, will enable AI to find new knowledge in health data. With the addition of AI, data quality assessed healthcare information has the potential to radically transform healthcare, through new clinical research discoveries and outcomes. As we move towards a learning healthcare system, one in which healthcare data flows to the research databases on which AI/ML techniques generate new knowledge, the proposed research considers what data quality issues arise in the eHealth domain and how can they be alleviated?

A possible focus for the work is requirements to enable clinical care data to automatically populate clinical registries. Currently, these are considered separate and registry data is considered ‘cleaner’. The second avenue of this PhD might look at whether and how ML techniques can take into account data quality metadata. as

Upon completion of the work the successful candidate will be in a position, as an expert on data quality for AI, to significantly improve the impact of AI and data analytics in the eHealth domain. They will also be in a position to work in this area in large data-centric ICT organisations in the health domain and elsewhere.

The successful candidate can avail of the opportunity to undertake their research as part of an interdisciplinary team of eHealth experts across the ADAPT institutions. The student will be co-supervised by Prof Gaye Stephens (TCD) and Prof Lucy Hederman (TCD) and Prof Damon Berry (TU Dublin).

Minimum qualifications

  • First-class honours undergraduate degree in computer science or similar discipline.

Preferred qualifications

  • MSc in computer science, eHealth or aligned field.
  • Skills: Programming, data science, eHealth

Application Process

As part of your application, you will be required to submit the following via 

  1. A Cover letter (800 words max)  including
    1. A personal letter of motivation, indicating why you wish to conduct this research project offered by ADAPT, and why you expect that you will be able to complete the research successfully; (500 words maximum)
    2. The letter should include a summary of your ideas (300 words maximum) for how you would approach the proposed research challenge with a specific focus on methods and processes for data quality assurance in the eHealth domain.
  2. Detailed curriculum vitae, including – if applicable – relevant publications;
    1. Details of your final year undergraduate project (if applicable)
    2. Details of your MSc project – Applicants without an MSc to provide evidence of any research experience.
    3. Details of any relevant modules previously taken, at undergraduate and/or Master level.
    4. Details of any relevant work experience (if applicable).
  3. Transcripts of degrees



ADAPT is committed to achieving better diversity and gender representation at all levels of the organisation, across leadership, academic, operations, research staff and studentship levels. ADAPT is committed to the continued development of employment policies, procedures and practices that promote gender equality. On that basis, we encourage and welcome talented people from all backgrounds to join ADAPT.

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