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factors assessment). You should hold a relevant PhD/DPhil (or near completion) and have publications in medical image analysis or computer vision video analysis. Knowledge of ultrasound imaging is not a
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of a collaborative team, led by Dr Sarah Morgan at the School of Biomedical Engineering and Imaging Sciences. The School is a world leading centre of expertise in AI for healthcare, providing
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project led by Professor Alison Noble (Institute of Biomedical Engineering) and Professor Aris Papageorghiou (Department of Women’s and Reproductive Health). This exciting and ambitious research aims
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, electrical polarisation and, then evaluate cell-matrix interactions using live-cell imaging, molecular assays and, spatial transcriptomic approaches to identify key mechanisms linking matrix mechanics
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learning for cardiovascular digital twins and AI-enabled precision treatment. The postholder will develop patient-specific models that integrate multimodal clinical, physiological, imaging and sensor data
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learning for cardiovascular digital twins and AI-enabled precision treatment. The postholder will develop patient-specific models that integrate multimodal clinical, physiological, imaging and sensor data
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within the device. The work combines advanced nanofabrication methods, such as electron-beam lithography and OLED fabrication via evaporation and solution-processing with sophisticated characterization
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, with the ability to work effectively at the engineering-biology interface. Hands-on experience of cleanroom micro- or nanofabrication, particularly silicon or porous-silicon processing, surface
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assessment). You should hold a relevant PhD/DPhil (or near completion) and have publications in medical image analysis or computer vision video analysis. Knowledge of ultrasound imaging is not a requirement
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Contract type: Fixed term for 12 months Hours: Full-time About the role We are seeking a Full-Time Postdoctoral Researcher in Computer Vision CT image analysis to join the Nuffield Department of Surgical