|Funding for:||UK Students, EU Students, International Students|
|Funding amount:||From £17,668 Home fees (2023/24) included plus an annual stipend paid at the UKRI rate (award for 2022/23).|
|Placed On:||20th September 2023|
|Closes:||16th October 2023|
Label-free Learning from Large-Scale Multi-Modal Medical Images and Its Application to Automated Diagnosis of Eye Diseases
Project contact: Prof Liangxiu Han
Home fees (2023/24) included plus an annual stipend paid at the UKRI rate (£17,668 for 2022/23).
Mode of study: Full time
Open to home and overseas students. Eligible overseas students will need to make up the difference in tuition fees.
Closing date: 16 October 2023
Expected start: January 2024
Artificial intelligence (AI) (particularly deep learning) has become the fundamental part of computer-aided medical diagnostics to aid clinical decision makings. As the disease has multiple risk factors, modern AI algorithms heavily rely on large well-annotated multimodal datasets. However, curating human labelled data at scale is expensive, daunting, and subject to individual bias.
This project proposes to include multiple modalities and aims to develop a novel SSL framework, capable of integrating the cross-modal information in the learned representation from unlabelled multi-modal images, with initial focus on its application to automated diagnosis of eye diseases.
Aims and objectives
Specific requirements of the project
Candidates must have a strong motivation for research and excellent programming skills. Expertise of developing computer vision and machine learning algorithms would be desirable, with an interest in image analysis.
How to apply (include weblink)
Interested applicants should contact Prof Liangxiu Han for an informal discussion.
To apply you will need to complete the online application form for a full-time PhD in Computing and digital technology (or download the PGR application form), by clicking the 'Apply' button, above.
You should also complete the PGR thesis proposal (supplementary information) form addressing the project’s aims and objectives, demonstrating how the skills you have maps to the area of research and why you see this area as being of importance and interest.
If applying online, you will need to upload your statement in the supporting documents section, or email the application form and statement to mailto:PGRAdmissions@mmu.ac.uk.
Closing date: 16 October 2023.
Expected start: January 2024.
Please quote the reference: SciEng-LH-2023-label-free-learning-2
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