Application Form
PhD Studentship in Health Identities [LHDMGS]

JobRef: 8905
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PhD Studentship in Health Identities [LHDMGS]

POSTED:April 12, 2021
CLOSES:July 9, 2021
Duration:4 Years
Reports to:Prof Damon Berry , Prof Gaye Stephens, Prof Lucy Hederman
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 


Health information is recorded about a wide range of real world entities, including patients, healthcare professionals, medical products, healthcare organisations and rooms. Less tangible entities such as orders, appointments, visits, plans, guidelines and standards are also part of health information.

To maximise the efficacy of AI reasoning about health information, reliable ‘digital twins’ of health-related identities need to be created. For reasons of data privacy, some of these identities may need to be anonymised before they are accessed by an AI.  

In order to assist a learning system to effectively integrate information from multiple sources, this work will create a format and metadata resources that

  • Enable recognition of the wide range of ‘digital twin’ identities, trait sets and identity domains that are implicitly embedded in legacy health systems
  • Provide high level ontological support to assist in explicitly relating identity instances of different types and to facilitate matching of identities of the same type across identity domains for the purposes of machine learning. 

The proposed PhD research will enable the successful applicant to become an expert in an area that is pivotal for the application of artificial intelligence and data analytics to the healthcare domain. Upon completion of the research, the candidate will be in a position to work in ICT organisations that seek to use large datasets in healthcare and other sectors to make new discoveries and improve healthcare outcomes 

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 Damon Berry (TU Dublin), Prof Gaye Stephens (TCD) and Prof Lucy Hederman (TCD). 

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 

Informal queries may be directed to Damon Barry, Gaye Stephens & Lucy Hederman   

Application Process

As part of your application you will be required to submit

  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 identity and ‘digital twins’ 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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