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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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methods to study human bone marrow models using high content imaging approaches. You will lead in designing and establishing new protocols to the laboratory as well as supporting, mentoring and training
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focused on developing tools for quantitative imaging of epithelial cell biology and biophysics. Moreover, you will support and develop novel workflows of bioimaging analysis to quantify advanced imaging
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in sustainability, photonic and quantum technologies, new nanostructured materials, sensing, imaging and clean energy. The group adopts an interdisciplinary approach to provide leading-edge research in
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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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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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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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or orthotopic tumour models Supporting preclinical treatment studies involving standard-of-care or experimental agents Applying in vivo imaging techniques (e.g., bioluminescence imaging) to monitor tumour
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Waite and team on the ‘Evaluating the Usability and Acceptability of a Prototype AI-Powered Recovery Pathway Progress Dashboard (AI-ERPP Dashboard) for Tracking Postoperative Recovery by Registered Nurses
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drugs. Areas of interest are: development of in vivo imaging assays for understanding efficacy of novel antifungal drugs, assay development, and determination of resistance liabilities of novel antifungal