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the above ‘Apply’ button. Please add only ‘Unsupervised Machine Learning for Cardiovascular Image Analysis’ in the research proposal box. Application deadline: 15th Sep 2025 (or until the position has been
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Early and accurate cancer detection remains a critical global healthcare challenge, with profound implications for patient outcomes and treatment strategies. While Time-of-Flight Positron Emission Tomography (ToF-PET) offers vital functional and molecular insights for improved cancer staging,...
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for 2025/26 academic year, increasing in line with inflation). Research training and support grant (RTSG) of £3000 per year. Funding is available for 4 years. Hours: Full Time Closes: Open until position
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with inflation). Research training and support grant (RTSG) of £3,000 per year. Funding is available for 4 years. Closes: Open until position filled The overarching aim of this project is to find
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early ‘prodromal’ stages) is yet to be established in large community settings. This PhD project will examine the effectiveness of AI-based analysis of eye images in predicting cognitive/neurodegenerative
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selection. Either upload a document or write into ‘Personal Statement’. Put code ‘TC118’ in ‘Studentship/Partnership Reference’. When prompted for research proposal, select ‘Write Proposal’. Type in the title
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The Biomedical Image Analysis Group, led by Prof Ben Glocker, in the Department of Computing at Imperial College London is seeking a talented Research Assistant / Associate to take a key role in an
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How many positions: 1 This 4-year PhD project is fully funded and home students, and EU students with settled status, are eligible to apply. The successful candidate will received an annual tax free
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) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
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Closing Date Sunday 17 August 2025 Reference PHD002-25 A funded PhD position is available on a project funded by the Leverhulme Trust. Description below: The density of information content in screen media