Applications are invited for a fully funded PhD studentship within a new multi-institutional, interdisciplinary national centre for data science and artificial intelligence funded by Research Ireland (Rinn Artificial Intelligence). The successful candidate will join a cohort-based PhD training programme spanning multiple Irish universities and research disciplines, providing a unique opportunity to undertake cutting-edge AI research while benefiting from a structured national training environment.

✅ Key details:
• €25,000 annual stipend for 4 years (tax free).
• Based at Trinity College Institute of Neuroscience
• Part of the Research Ireland AI Centre national PhD programme

🚨 Closing date: 26 June 2026 (12 noon Irish time)

➡️ Visit the google form here to apply: Application form for PhD studentships in a national initiative for data science and AI funded by Research Ireland

Or Scan the QR code to apply.

📨Please also email your enquiries and your application to the joint supervisors, including 'Research Ireland AI centre PhD application' in the subject line:
• Prof Jane McGrath, Associate Professor of Child Psychiatry, TCD: jane.mcgrath@tcd.ie
• Prof Robert Whelan, Professor in Psychology, TCD: robert.whelan@tcd.ie

Please note: Due to the expected high number of applications, only shortlisted candidates will be contacted. Those invited to interview will be requested to give a 10 minute presentation comprised of a 5 minute presentation on their career to date and a 5 minute presentation entitled “AI in ADHD”

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This PhD project will develop and evaluate explainable artificial intelligence (XAI) approaches to support clinical decision-making in Attention-Deficit/Hyperactivity Disorder (ADHD).

The research is embedded within specialist Child and Adolescent Mental Health Services (CAMHS) in the HSE and will use routinely collected clinical data, including information on symptom profiles, comorbidities, medication exposure, and treatment outcomes. A key aim is to apply modern Artificial Intelligence methods to identify clinically meaningful patterns in heterogeneous clinical populations and to develop predictive models of treatment response and clinical trajectories.