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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual
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efficient for medicine? If the answer is yes, please continue reading! Join our team! We are looking for a PhD student to work on the topic of shape analysis for medical imaging, tailored for deep learning
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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A fully funded 3.5 years PhD position in the field of experimental nanoscience at surfaces and molecular imaging of conjugated polymers is available in the group of Prof. Giovanni Costantini at UoB
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focus on research and development in Atmospheric Pressure Matrix-Assisted Laser Desorption/Ionization (AP-MALDI) mass spectrometry and molecular imaging, using high-resolution Orbitrap MS instrumentation
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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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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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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 the UKRI rate (£20,780 for 2025/26) and tuition fees will be paid. We expect the stipend to...
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available