Do you want to apply your data analysis skills to identify children at risk of not being in education, employment or training (NEET)? Are you motivated to work with an ambitious team seeking to design interventions to improve children’s life outcomes? Are you interested in the process of connecting big routine datasets?

We are seeking a highly motivated individual to join the Connected Bradford NEET project at the University of Leeds and Bradford Institute for Health Research (BIHR), funded by a generous donation from an invested Alumna.

Based at BIHR on the Bradford Royal Infirmary campus, you will be responsible for designing a programme of work to identify young people who are at risk of becoming NEET and developing suitable interventions. Using the data available through the Connected Bradford dataset, you will conduct analyses to verify these risk factors. You will link data provided by the Department for Education with data you deem relevant, e.g. mental health data provided by the Bradford District Care Trust and vulnerability data provided by the Bradford Metropolitan District Council. Additionally, you will identify and contribute to the sourcing of key routine data that is not currently a part of the Connected Bradford dataset, which would enable your analysis.

You may also undertake tasks related to the wider Connected Bradford project, such as cleaning other datasets and making them research-ready using best practices in open science research.

To explore the post further or for any queries you may have, please contact: 

Professor Mark Mon-Williams Email: [email protected]

Interviews are scheduled to take place on 31 August 2022

As an international research-intensive university, we welcome students and staff from all walks of life and from across the world. We foster an inclusive environment where all can flourish and prosper, and we are proud of our strong commitment to student education. Within the School of Psychology we are dedicated to diversifying our community and we welcome the unique contributions that individuals can bring, and particularly encourage applications from, but not limited to Black, Asian, people who belong to a minority ethnic community, people who identify as LGBT+; and people with disabilities. Candidates will always be selected based on merit and ability.