PhD Studentship in building responsible AI-informed digital tools for diagnostics and signposting in

University of Cambridge; Cambridge; On-site; GBP 18,000 - 20,000; Full time

Job summary

A leading UK university is offering a fully funded PhD studentship focused on developing AI-informed tools for early identification of mental health issues in children. The successful candidate will work under expert supervision, gaining experience in clinical data science and ethical AI. Applications are due by 2nd October 2025, including academic transcripts and references. This opportunity is part of a critical research programme aimed at improving mental health outcomes for children.

Qualifications

• Experience in developing machine learning algorithms.
• Familiarity with clinical data science approaches.
• Background in AI, implementation science, or digital health innovation.

Responsibilities

• Develop AI tools to identify mental health issues in children.
• Validate algorithms using longitudinal datasets.
• Work within the THRIVE framework for mental health.

Skills

Machine learning

Clinical data science

Systems engineering

Ethical AI development

User-friendly tool design

Education

Relevant undergraduate degree

Job description

Overview

This PhD is funded by the NIHR HealthTech Research Centre in Paediatrics and Child Health. It is hosted by the Timely Group (PI Dr Anna Moore). We invite applications for a fully funded PhD studentship in developing responsible AI-informed tools for use in child mental health pathways to support the early identification of mental health problems in children. The post is based in the Department of Psychiatry, commencing in January 2026. This studentship will be under the supervision of Assistant Professor Anna Moore and Professor Zoe Kourtzi (Department of Psychology). The purpose of this PhD is to build early identification tools for childhood anxiety and depression for implementation in clinical pathways. The tools will be designed based on the THRIVE model for children\'s mental health. Professor Andrew Flewitt from Dept of Engineering will act as an Advisor in Systems Engineering and Professor Peter Fonagy (UCL) will act as an advisor as a key THRIVE author.

Timely Group

The Timely Group at the University of Cambridge, Dept. of Psychiatry is led by Dr. Anna Moore, a UKRI Future Leaders Fellow and Assistant Professor in Child Psychiatry and Medical Informatics. Timely is developing innovative approaches to children\'s mental health through the integration of data science, implementation science and clinical practice. Timely addresses a critical challenge: 70% of children suffering from mental health problems cannot access appropriate services, and those who do face unprecedented waiting times. This research programme aims to revolutionise childhood mental health services through the development of responsible AI-powered digital tools that enable early identification and personalised signposting to evidence-based interventions, improving access to support. The Timely group has led the development of CADRE (Child and Adolescent Data Resource), the first federated multi-agency data platform for children\'s mental health research. CADRE enables secure analysis of longitudinal data from health, education and social care across multiple trusts and regions. The Timely program is funded by a UKRI Future Leaders Fellowship, DataMind and the NIHR Mental Health Translational Research Collaboration and CADRE is part of the NIHR Mental Health Secure Data Environment.

The PhD Project

This PhD project will focus on developing and validating AI tools aligned to the THRIVE framework (Wolpert et al), which will aim to identify depression and anxiety in children and young people, and signpost them to appropriate support based on their needs and preferences for help and support. [Please note, this project is not about building mental health interventions, and so applications should not be focussed on this.] The student will work on creating one of two tools: either designed for use in primary care settings where GPs often struggle to identify mental health needs, or one for children on ASD/ADHD waiting lists who frequently experience unrecognised depression and anxiety whilst facing barriers to accessing mental health support. The project will involve developing and externally validating machine learning algorithms using CADRE\'s rich longitudinal datasets, and taking systems engineering approaches to ensure tools are practical and user-friendly. The work will take an ethical AI development appraoch, ensuring the tools are transparent, interpretable, and equitable across diverse populations. The student will gain expertise in federated analytics, clinical data science, systems engineering, implementation science, and digital health innovation whilst contributing to research that has direct potential for real-world impact in improving mental health outcomes for children and young people.

How to apply

All applications should be made online via the University\'s Applicant Portal for a PhD in Psychiatry, naming Dr Anna Moore and the project within the application. Applications should include academic transcripts, CV, statement of purpose (within the online application) and 2 references. An application is only complete when all supporting documents, including the 2 academic references, are submitted. It is the applicant\'s responsibility to ensure their referees submit their references before the closing date. Please also explain your motivation why you wish to pursue a PhD in this area, outline your research interests and background, and describe the qualities and experience you will bring to the role. For informal enquiries, please contact Dr Anna Moore ([e-mail]).

Closing Date: 2nd October 2025

Benefits and Eligibility

The University actively supports equality, diversity, and inclusion and encourages applications from all sections of society. The University has a responsibility to ensure that all employees are eligible to live and work in the UK.