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processes that underly normal and abnormal cardiovascular and metabolic function and drive the translation of this strong basic science into advances in clinical practice. Our community of world-renowned
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this date, in both directions). The position is funded by NERC grant 'High Resolution Radar Imaging of Pyroclastic Density Currents', in collaboration with University College London, and the University
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cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering; transplantation immunology; pharmaceutical science; physiology and
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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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it relates to the laser process parameters. Specifically, you will carry out high resolution Raman imaging on laser written polymer networks with liquid crystal resins. Additionally, you will develop
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in and knowledge of the broad area of soft matter, with expertise in microscopy, optical imaging, and data analysis. Experience in building and working with optical traps, and familiarity with colloid
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understanding of the polymer network morphology and how it relates to the laser process parameters. Specifically, you will carry out high resolution Raman imaging on laser written polymer networks with liquid
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soft matter, with expertise in microscopy, optical imaging, and data analysis. Experience in building and working with optical traps, and familiarity with colloid chemistry and surface functionalisation
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on autofluorescence (AF) imaging and Raman spectroscopy for detection of metastatic lymph nodes during breast cancer surgery. Engaging with and reporting to Dr Alexey A. Koloydenko (Department of
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for conditions such as otosclerosis. The position requires expertise in medical image analysis, proficiency with neural network architectures (particularly CNNs for segmentation tasks), and experience processing