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economy and offers a vibrant and exciting environment for postgraduate training amongst international world experts. PhD positions are available in 28 different research groups in diverse areas covering
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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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using nano-vibration detection and super-resolution imaging. Funded by the Royal Society APEX Award (with support from the Royal Society, British Academy, Royal Academy of Engineering, and Leverhulme
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Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country United Kingdom Application Deadline 16 Oct 2025 - 23:59 (Europe/London) Type of Contract Temporary Job Status Full-time Offer
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How to apply: uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded for home students or EU students with settled status; the successful candidate will receive a tax-free stipend set at
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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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Open to: UK fee eligible applicants only Funding providers: EPSRC and LaVision UK Ltd Subject areas: Biomedical Engineering, Experimental Mechanics, Image-Based Measurements, Biomechanics Project
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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