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publications in medical image analysis or computer vision video analysis. Knowledge of ultrasound imaging is not a requirement but an interest in research at the interface of machine learning with real-world
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We are seeking a creative and highly motivated postdoctoral researcher to join the CAIFE study, a joint project led by Professor Alison Noble (Institute of Biomedical Engineering) and Professor Aris
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evaluating computational methods, analysing imaging data, collaborating with clinicians for real-world impact, and contributing to publications. About You PhD (or near completion) in computer science
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biochemical work with proteins and DNA will be highly rated in the selection process. The ideal candidate will have recently obtained a PhD in physics, biophysics, biochemistry, physical chemistry, engineering
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, integrate device engineering with clinical workflows, and apply artificial intelligence and machine learning for automated image and signal analysis, tissue classification, and real-time diagnostics
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this condition. You will evaluate their interactions using in vivo micro-CT, intravital imaging, spatial transcriptomics and molecular analysis techniques, identifying the key pathways governing this process
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this condition. You will evaluate their interactions using in vivo micro-CT, intravital imaging, spatial transcriptomics and molecular analysis techniques, identifying the key pathways governing this process
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soft matter, with expertise in microscopy, optical imaging, and data analysis. Experience in building and working with optical traps will be highly rated in the selection process. The project also
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well as an appropriate multidisciplinary PhD Must-have background: · Strong experience in X-ray imaging, tomography or closely related 3D X-ray methods. · Experience with reconstruction, scientific coding and
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About the Role This is an exciting position where applicants are invited to join a multi-disciplinary team of bioengineers, biomedical scientists, and computer scientists working together at Queen