King's College London
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PhD in Trustworthy Generative AI in Healthcare King’s College London in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableCountry
United Kingdom
University
King's College London

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About this position
PhD opportunity: Trustworthy Generative AI in Healthcare at King’s College London, based in the Centre for Oral, Clinical & Translational Sciences and the Translational AI Research (TAIR) Lab.
This funded PhD project focuses on statistical machine learning, multimodal large language models, uncertainty-aware AI, and 3D medical imaging. The research aims to develop and evaluate generative and vision-language models that combine medical images, video, and tabular clinical data for disease detection, prediction, and decision making.
The project emphasizes trustworthiness in high-stakes clinical settings, including calibrated uncertainty, robustness under distribution shift, and rigorous evaluation frameworks. Applications are drawn from oral and wider healthcare, including radiographic interpretation and clinical record analysis, with collaboration alongside clinicians in the Faculty of Dentistry, Oral & Craniofacial Sciences.
Supervision is by Dr Yunpeng Li and Dr Yali Du. The project also offers wider access to resources across King’s, including the Department of Informatics in the Faculty of Natural, Mathematical & Engineering Sciences.
Funding: one fully funded PhD studentship. Home or international fees are covered, and a stipend is paid at the UKRI London rate.
Eligibility: open to UK and international applicants. Prior knowledge of dentistry or medicine is not required.
Applications: accepted all year round. Interested candidates should visit the institution website for full details and to apply.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
More information can be found here
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