Organisation/Company UNIVERSITY OF SOUTHAMPTON Research Field Other Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Country United Kingdom Application Deadline 10 Apr 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
Offer Description
About the Project
This project investigates the use of artificial intelligence (AI) tools in the NHS for diagnosing mental health conditions, particularly in individuals with multiple long-term conditions (MLTC). It aims to assess the potential for AI tools to exacerbate disparities based on sociodemographic factors such as age, sex, ethnicity, and socio-economic status. We will be cataloguing AI tools used in clinical settings and evaluating a selected subset using data from the Clinical Practice Research Datalink (CPRD). The research is funded by the NIHR through the MLTC Cross NIHR Collaboration, aligning with the NIHR Strategic Framework for MLTC Research.
The work will be based within the Big Data in Health Group (BDiH) at the University of Southampton, led by Dr. Hajira Dambha-Miller, and involves collaboration with the NIHR CNC methodologies team.
About the Role
Experience in analysing CPRD is essential. You will primarily be responsible for conducting CPRD analyses. The role requires strong organisational skills, independence, and proficiency in statistical analysis or epidemiology. You will also be expected to present findings using interactive visualisations. This position is initially funded until 31st December 2025 with potential for extension.
About You
We are seeking a candidate with experience in CPRD. Excellent written and verbal English is required, and the ability to work independently. If you meet these requirements, we invite you to join our dynamic and supportive research group.
Please note, shortlisted applicants will be invited to interview and be required to complete a short pre-interview assessment.
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