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scientists, and researchers working on medical image analysis, machine learning, and audiology. Our recent work has focused on using deep learning to analyse temporal bone CT scans and brain MRI data in
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experts to acquire bespoke training and testing data; develop prototype solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated
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Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based on autofluorescence (AF) imaging
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and statistical modelling, statistical image analysis and computer vision, chemometrics, biophysics, bioengineering. Preference will be given to candidates with a demonstrated experience in applying
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We are seeking a talented, organised, and highly motivated individual to join the Department of Eye and Vision Sciences at the University of Liverpool as a Postdoctoral Research Associate, funded by
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solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated and real clinical scenarios. Evaluation may involve quantitative studies
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immunohistochemistry, along with experience in fluorescent microscopy, image capture and Adobe photoshop are also essential. Main duties and responsibilities Carry out research/experiments. The main duty is to perform
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immunohistochemistry, along with experience in experience in fluorescent microscopy, image capture and Adobe photoshop are also essential. Main duties and responsibilities Carry out research/experiments. The main duty
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of the collaborative interdisciplinary nature of our research, which also includes strong industrial partnerships. The strategic vision for the Department includes a major growth over the next five years, with a
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across the Respiratory Science disciplines with a vision to eliminate lung disease by prevention, early diagnosis and improved treatments. We are leading the field in understanding mechanisms of disease