Postdoctoral Statistician — CYP Health Analytics
Cambridgeshire and Peterborough NHS Foundation Trust
Cambridge, CB2 0SZ
Salary
£49,387 to £56,515
Contract
Fixed-Term
Hours
Not specified
Closing date
2 September 2026
2 days left
Job description
Launching in summer 2026, CADRE (the Children and Adolescents Data Resource) is being developed as a whole-population, multi-agency, longitudinal link...
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.
Cambridgeshire and Peterborough NHS Foundation Trust is a health and social care organisation dedicated to providing high quality care with compassion to improve the health and wellbeing of the people we care for, as well as supporting and empowering them to lead fulfilling lives.
Our clinical teams deliver a wide range of NHS services across inpatient, primary care and community settings, including children's, adult and older people's mental health, forensic and specialist mental health, learning disabilities, primary care and liaison psychiatry, substance misuse, social care, and research and development.
To achieve our goals, we recruit high calibre candidates who share our vision and values. As an equal opportunities' employer, we welcome applications from all sections of the community, particularly under represented groups including people with long term conditions and members of our ethnic minority and LGBTQ+ communities.
All appointments for new employees to CPFT are subject to the successful completion of a probationary period.
Please note we reserve the right to close adverts early should we receive sufficient applications.
Regrettably, we cannot offer sponsorship for all roles. If you apply for a post that does not attract sponsorship, your application will be withdrawn from the process.
For further information on CPFT, please visit our website at https://www.cpft.nhs.uk
Education / Qualifications
Essential
- PhD in a quantitative discipline relevant to health data science (e.g. epidemiology, biostatistics, computer science, mathematics, public health, or a clinical discipline with strong quantitative training). Ideally with 4+ years' postdoc experience.
Experience
Essential
- Experience analysing large, complex, routinely collected health datasets (e.g. electronic health records, administrative data, or multi-agency linked data)
- Demonstrated experience with SQL and working with relational databases
- Strong grounding in epidemiological methods, including cohort analysis, prevalence and incidence estimation, and longitudinal study design
- Experience with statistical modelling (e.g. multi-level regression, generalised linear models, time-series or survival analysis)
Desirable
- Understanding of UK health data infrastructure (e.g. NHS datasets, OMOP CDM, SAIL, CPRD)
- Experience working with children and young people's health, education, or social care data
- Familiarity with Trusted Research Environments (TREs), safe havens, or other secure data access frameworks
- Applied experience with machine learning and/or AI approaches for prediction or classification in health data contexts
Knowledge & Skills
Essential
- Proficiency in Python and/or R to a high standard
- Experience with version control (e.g. Git) and collaborative code environments
- Ability to communicate complex analytical findings clearly to clinical, research, operational, and non-technical audiences
- Strong scientific writing skills evidenced by peer-reviewed publication, pre-prints or submitted manuscripts
Desirable
- Ability to construct, document, and maintain analytical pipelines for large datasets
- Experience with federated analytics, privacy-preserving analytical methods, or distributed data environments (e.g. Bitfount, DataSHIELD, or similar platforms)
- Ability to work collaboratively within a multidisciplinary team, including peer working with other postdoctoral researchers and contributing to the supervision of research assistants and postgraduate students
- Experience presenting at academic or professional conferences
Personal Qualities
Essential
- Self-motivated and able to manage own workload and timelines within a fast-paced research environment
- Commitment to rigorous, reproducible, and ethically conducted research
- Enthusiasm for translational research with direct impact on children's health and wellbeing
Desirable
- Communicates effectively and appropriately with senior management, external partners and with people at all levels across the University and outside the University in the wider community
- Supports, promotes and implements change; encourages the adoption of new methods and overcomes barriers to acceptance
- Encourages and facilitates the learning and development of others; demonstrates enhancement of individual and team potential through giving clear direction, guidance and feedback on performance
- Develops and maintains existing partnerships; identifies means of enhancing team effectiveness
How to apply
Applications are handled entirely by the employer on the original advert. We do not collect CVs, supporting statements or application data.
Provenance
Source
NHS Jobs
First seen
19 August 2026
Last checked
21 August 2026
Salary, closing date and description are taken from the employer's advert. The original advert always takes precedence.
About the employer
NHS organisation
This listing was structured from NHS Jobs. Vacancy details and the application process remain the responsibility of the original source.
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