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Sara Atito

4 days ago

Fully Funded PhD in Medical Multimodal Language Models and Alignment University of Surrey in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded for 3.5 years, including tuition and stipend.

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Country

United Kingdom

University

University of Surrey

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Keywords

Computer Science
Biomedical Engineering
Medical Imaging
Biology
Medical Science
Explainable Ai
Self-supervised Learning
Omics
Genomic
Statistics
ML

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About this position

Fully funded PhD opportunity at the University of Surrey in medical multimodal language models and alignment methods for trustworthy healthcare AI.

The project focuses on developing methods that improve alignment between heterogeneous medical modalities and language outputs, aiming to reduce hallucinations and produce grounded, reliable reports. Research topics include medical imaging, radiology, genomics/multiomics, clinical time-series, multimodal foundation models, self-supervised learning, statistical genetics, and medical AI.

You will join an interdisciplinary supervisory environment with collaborations across AI and biosciences. The post is described as fully funded for 3.5 years, covering tuition plus stipend.

Eligibility highlights: applicants should have a strong background in ML/AI. The post is open to UK citizens only. Intake is expected in January or April 2027.

To apply, contact Sara Atito by email and share your background and interest in trustworthy multimodal medical AI.

Funding details

Fully funded for 3.5 years, including tuition and stipend.

What's required

Open to UK citizens only. Applicants should have a strong background in ML/AI and an interest in trustworthy multimodal medical AI. The project is suited to candidates interested in multimodal foundation models, self-supervised learning, statistical genetics, medical imaging, genomics, and clinical time-series data.

How to apply

Email Sara Atito directly to express interest and discuss the PhD opportunity. Mention your ML/AI background and fit for trustworthy multimodal medical AI.

More information can be found here

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