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University of Southampton

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PhD in Trustworthy AI for Personalised Disease Risk Prediction using Genetic and Clinical Data University of Southampton in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Competition funded PhD project. The page indicates funding is available through the competition-funded route; no stipend amount or tuition details are stated in the post text.

Deadline

Jun 17, 2027

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Country

United Kingdom

University

University of Southampton

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Keywords

Computer Science
Biology
Uncertainty Analysis
Medical Science
Salud Pública
Genetic Epidemiology
Clinical Data
Type 2 Diabetes
Statistics
Statistical Modelling
ML

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About this position

PhD project at the University of Southampton on Trustworthy AI for personalised disease risk prediction using genetic and clinical data.

This research sits at the intersection of computer science, statistics, genetic epidemiology, and medical science. The project aims to develop uncertainty-aware statistical and machine learning methods for personalised disease risk prediction, combining genetic information, clinical measurements, and potentially longitudinal health data.

Key research themes include multimodal risk prediction, uncertainty quantification, and reliable decision support. The primary application area is metabolic diseases, especially type 2 diabetes and obesity-related complications. You will work with population-based and clinical datasets, simulation studies, and methods for assessing prediction accuracy, calibration, bias, and uncertainty.

Training includes statistical modelling, machine learning, genetic epidemiology, uncertainty quantification, analysis of large-scale genetic and longitudinal clinical datasets, and reproducible research practices. The project also offers support for scientific writing, conference presentations, collaboration, and career development.

Entry requirement: at least a 2:1 honours degree. The project is competition funded. Closing date: 17 June 2027.

Funding details

Competition funded PhD project. The page indicates funding is available through the competition-funded route; no stipend amount or tuition details are stated in the post text.

What's required

Applicants should have at least a 2:1 honours degree. The project is suited to candidates interested in statistical modelling, machine learning, genetic epidemiology, uncertainty quantification, large-scale genetic and longitudinal clinical datasets, simulation studies, prediction reliability, bias assessment, and reproducible research practices.

How to apply

Review the project details and full entry requirements on the University of Southampton page, then apply through the postgraduate research application process linked from the project page. Check the funding and fees section before submitting your application.

More information can be found here

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