Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

PhD Studentship: Developing digital tools to support a personalised preventative pathway for children's mental health

University of Cambridge
Cambridge
1 year ago
Applications closed

Related Jobs

View all jobs

PhD Studentship: NIHR UCL UCLH BRC studentships in AI in medicine and health data science

EPSRC CDT Machine Learning Systems Fully-Funded PhD Programme

PhD Position in Applied Cryptography and Secure Machine Learning (Suitable for UK Candidats)

AdTech Data Scientist for Global Gaming Marketing

Machine Learning Research Engineer

Principal Data Scientist: Recommender & Personalization Lead

Based within the Timely Research Group, Department of Psychiatry, University of Cambridge

A full scholarship funded through Peterhouse, University of Cambridge

The studentship will be hosted within the Timely Research Group, Department of Psychiatry. The Department has an outstanding international reputation in research, rated the best psychiatry department in the UK and in Europe, and has excelled in the last three Research Assessment Exercises. The University of Cambridge is consistently ranked among the very top universities in the world.

The Timely project aims to develop digitally supported personalised prevention pathways for children's mental health services. Baseline work has been carried out to construct a linked, population-level, multi-agency, longitudinal database including administrative and clinical records from health, education and social care records. A blueprint for a preventative pathway has been developed. This project will take forward the blueprint, refine it with a broad range of stakeholders including children and families, and co-develop detailed specifications for AI-driven digital tools. Particular attention will be placed on taking a responsible AI approach.

We are particularly interested in candidates who would like to use large longitudinal datasets to investigate how heterogeneous factors contribute to differences in neurodevelopmental and mental health conditions. As a part of the PhD, candidates will build complex longitudinal models to investigate the role of a range of factors, investigating their correlation and interaction. This knowledge will be used to develop responsible AI tools and validate them, with particular attention to ensuring they are equitable and do not exacerbate or create bias in the delivery of care. Candidates will develop skills to handle large-scale datasets, longitudinal modelling, handling electronic heath records, and develop their knowledge of AI and machine learning. Candidates are asked to submit a potential project title and a research proposal within this research area.

Applicants for the Studentships should have, or expect to gain a 1st class or a high 2.1 class Honours degree in a relevant discipline, and may also have completed further research training or a Master's degree. The stipend will be paid for the 3-year duration of the award. Only the fees for home students will be met in full. In addition, the Studentship includes modest funding for running costs of the research and costs for travel to scientific conferences.

An academic CV. A research proposal within this research area (maximum 2000 words, excluding bibliography or figures). A cover letter indicating a brief summary of your research interests, any completed research conducted, interests and skills in statistical methods, analyses of large datasets, and coding, and a clear statement of your eligibility for this funding award.

Applications must be received by midnight onOctober 31st 2024. Interviews will be held within a month of the application deadline.

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.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.