Postdoctoral Statistician — CYP Health Analytics

Job overview

Launching in summer 2026, CADRE (the Children and Adolescents Data Resource) is being developed as a whole-population, multi-agency, longitudinal linked data platform for children and young people (CYP) aged 0–24. The platform will integrate health, social care, education and environmental data.

CADRE will be an important infrastructure project for the forthcoming Cambridge Children’s Hospital (opening 2030). It will hold de-identified records for approximately one million children across Cambridgeshire and Peterborough — with 15 years of longitudinal data — and will expand to sites in Greater Manchester, Liverpool, and Birmingham. As new regions are added, analyses and model development will be conducted using privacy-preserving federated analytics.

The postholder will develop a research programme based on the data available within the broader CADRE programme with the aim of developing and answering key questions and publishing them.

This is an outstanding opportunity for a statistician wishing to play a leading role in developing a research programme at the intersection of health informatics, epidemiology, and applied machine learning.

Main duties of the job

The postholder will be an integral member of the CADRE research team, contributing to the quantitative analysis programme using the platform’s pseudonymised linked dataset. Working alongside colleagues responsible for data pipeline and quality infrastructure, the postholder will focus on longitudinal and predictive analyses of CYP health, contributing to peer-reviewed publications, grant applications, and the development of a clinical risk stratification tool for early identification of CYP at risk of mental health problems prior to first contact with services.

The role is highly collaborative and will involve close working with clinical, engineering, and operational colleagues across CADRE’s partner institutions, as well as with academic and NHS co-investigators. Although employed by Cambridgeshire and Peterborough NHS Foundation Trust (CPFT), the postholder will be based with the CADRE team in the Department of Psychiatry, University of Cambridge, on the Addenbrooke’s site. The postholder will have access to the full CADRE platform, including its Trusted Research Environment and federated analytics capability.

The postholder will join a small, expert team and, as it grows, will have access to one of the most comprehensive linked datasets for children and young people’s health in the UK.

Detailed job description and main responsibilities

Please refer to the attached job description and person specification for full details of responsibilities.

Working with data prepared and quality-assured by the CADRE data engineering team, the postholder will contribute to longitudinal analyses of the cohort, including:

• Describing the cohort at index event (first contact with health, education, or social care services), including individual characteristics, service type, assessment outcomes, diagnoses, and severity measures.
• Estimating the prevalence and incidence of diagnoses and identified needs longitudinally, and examining how these differ across health and care settings.
• Conducting time-to-event analyses examining delays to diagnosis or treatment following initial presentation.
• Measuring candidate risk and protective factors, exploring sub-group structure and clustering.
• Exploring relationships between variables and carrying out feature engineering steps required to support predictive modelling. The postholder will develop and validate predictive models aimed at:
• Modelling future risk of mental health problems in CYP prior to contact with mental health or social care services.
• Identifying early signs of existing mental health problems within routinely collected multi-agency data.
• Exploring optimal intervention matching based on identified need profiles.
• Comparing and evaluating traditional statistical approaches (e.g. multi-level regression, generalised linear models, survival analysis) alongside machine learning and AI methods, selecting approaches appropriate to the research question and data structure.
• Prepare high-quality manuscripts for peer-reviewed publication across statistical, clinical, and public health journals.
• Contributing to the development of a validated risk stratification tool suitable for integration into clinical pathways and for use as an enrichment strategy for randomised controlled trials.

Applicant requirements

The postholder will have access to vulnerable people in the course of their normal duties and as such this post is subject to the Rehabilitation of Offenders Act 1974 (Exceptions) Order 1975 (Amendment) (England and Wales) Order 2020 and as such it will be necessary for a submission for Disclosure to be made to the Disclosure and Barring Service to check for any previous criminal convictions.