Closing date: 02 February 2026
Open to: UK and international applicants
Funding providers: Faculty of Science and Engineering and Cardiff & Vale UHB
The subject areas: NLP, Machine Learning, Big Data, Paediatric
The Project start dates: 1 April 2026 **Please see the note below regarding potential later start dates
Supervisors: Primary supervisor: Dr. Trang Doan, Swansea University, Secondary supervisor: Dr. Deepak Sahoo, Swansea University
Additional supervisory team members:
Rhian Thomas-turner, Head of Children's Research Operations and Strategy, Cardiff & Vale UHB
Angela Strang, Research Development & Trial manager in CYARU, Cardiff & Vale UHB
Aligned programme of study: PhD in Computer Science
Mode of study: Full-time
Place of Study: The successful candidate is expected to work closely with the relevant medical staff at Cardiff & Vale UHB.
Project Description:
This PhD project aims to transform paediatric healthcare by addressing critical data and research gaps through advanced artificial intelligence (AI). Despite its importance, paediatric healthcare remains under-researched, particularly in areas like rare diseases, neonatal care, and chronic conditions. A major barrier is the lack of AI-ready data due to a lack of electronic health records (EHR) in Wales, meaning most paediatric records are handwritten and unstructured
The project will prioritise digitising these records using natural language processing (NLP) and machine learning (ML) to create structured datasets. These will support AI applications in paediatric care, enabling early detection of conditions and personalised treatment planning.
A human-in-the-loop (HITL) approach will ensure clinical expertise guides model development, improving accuracy and trust. Ethical considerations, including data privacy and collaboration with hospital ethics boards, are central to the project. Ultimately, this research seeks to produce AI-ready data creation techniques that will help establish scalable, globally relevant AI solutions and elevate paediatric healthcare to the standards seen in adult medicine.
The ideal candidate should have background in one of the Machine Learning or Data Science domains with high motivation for upskilling and filling any gaps in their knowledge based on the requirements of the project at the early stages of the study.
Funding Duration - 4 years
For more details please see here: https://www.swansea.ac.uk/postgraduate/scholarships/research/computer-science-fse-cardiff-vale-uhb-artificial-intelligence-phd-2025-rs933.php
International Students – Fully funded if the applicant is successful in being offered a SUIPRES Scholarship as outlined below.
Swansea University is pleased to offer the Swansea University International Postgraduate Research Excellence Scholarship (SUIPRES). This is a competitively awarded Scholarship open to overseas PhD and Professional Doctorate applicants eligible for the international rate of tuition fees who can demonstrate excellence in academic achievement.
The SUIPRES Scholarship covers the difference between the International and the Home tuition fee for the duration of the PhD/Professional Doctorate programme. Successful candidates will be charged fees aligned to the UK rate per year. The scholarship will be offset against your tuition fee liability
All International applications will be considered for a SUIPRES Scholarship. You will be informed whether a SUIPRES Scholarship will be offered within your offer letter.
PhD: Applicants for PhD must hold an undergraduate degree at 2.1 level in Computer Science, Mathematics or a closely related discipline, or an appropriate master’s degree with a minimum overall grade at ‘Merit’ (or Non-UK equivalent as defined by Swansea University).
English Language
IELTS 6.5 Overall (with no individual component below 6.0) or Swansea University recognised equivalent. Full details of our English Language policy, including certificate time validity, can be found here.
Note for international and European applicants: details of how your qualification compares to the published academic entry requirements can be found on our Country Specific Entry Requirements page.
Please note that the programme requires some applicants to hold ATAS clearance, further details on ATAS scheme eligibility are available on the UK Government website.
ATAS clearance IS NOT required to be held as part of the scholarship application process. Successful award winners (as appropriate) are provided with details as to how to apply for ATAS clearance in tandem with a scholarship course offer.
Funding
This scholarship covers the full cost of tuition fees and an annual stipend at UKRI rate (currently £20,780 for 2025-26) for 4 years.
Additional research expenses of up to £1,000 per annum will also be available.
To apply, please complete the entire application form
In order to be considered for this scholarship award the following steps are also required.
1) In section ‘Programme Related Information’ please input the relevant RS Code for the scholarship award i.e. RS933
2) In section ‘Research’ you will see ‘Proposed project title/studentship title’* (Mandatory)
3) In section ‘Funding information’ please choose the option ‘Scholarship Funding’ only. Please ensure no other options are selected.
*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.
If you’ve previously applied for this programme, the system will display an “Application Submitted” warning and block a new submission. In this case:
One application is required per individual Swansea University led research scholarship award; applications cannot be considered listing multiple Swansea University led research scholarship awards.
NOTE: Applicants for PhD/EngD/ProfD/EdD - to support our commitment to providing an environment free of discrimination and celebrating diversity at Swansea University you are required to complete an Equality, Diversity and Inclusion (EDI) Monitoring Form in addition to your programme application form.
Please note that completion of the EDI Monitoring Form is mandatory; your application may not progress if this information is not submitted.
As part of your online application, you MUST upload the following documents (please do not send these via email):
Informal enquiries are welcome; please contact
Dr. Trang Doan, [email protected]
Dr. Deepak Sahoo, [email protected]
*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.
** In exceptional circumstances, and subject to the discretion of the University and/or the relevant funding body, a deferral of offer may be granted to the next available enrolment period. Such deferral will typically not exceed a duration of three calendar months from the originally stipulated commencement date. Please note that only one deferral may be considered, and any such deferral is not guaranteed.
Open to: UK and international applicants
International Students – Fully funded if the applicant is successful in being offered a SUIPRES Scholarship
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