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of clinicians, computer scientists, mathematicians, statisticians and biologists to ensure clinical AI is developed with close consideration of clinical constraints and workflows. To direct and provide academic
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system by adding, tracking and validating asset information, including maintenance records, performance data, images and historical information. Using data analytics to make informed decisions about asset
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TriboLab and visualising underlying processes using a custom-made, in-situ optical microscopy technique. Analyse results, including visualising corelations between frictional behaviour and recorded images
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Assistant who will help investigate how epithelia responds to crowding to trigger extrusion. Our lab identified cell extrusion as a critical process driving epithelial cell death. Importantly, excess crowding
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delivered in partnership with colleagues in the Faculty of Life Sciences and Medicine (e.g. School of Immunology & Microbial Sciences, School of Biomedical Engineering & Imaging Sciences) and beyond. In
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the team with track record and experience in neural tissue engineering, axonal biology, microfabrication and live imaging microscopy to advance a number of research projects within the lab and co-manage
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the team with track record and experience in neural tissue engineering, axonal biology, microfabrication and live imaging microscopy to advance a number of research projects within the lab and co-manage
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. Established to provide a single interface for those wishing to conduct clinical research within the partner organisations, and to ensure that there are common, efficient processes for the set up and
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(RV) and Adeno-Associated Viral Vector (AAV) production for early-phase clinical trials, alongside substantial programmes in process innovation, knowledge transfer and training to address critical
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training opportunities for students to successfully undertake Research in Practice activities; to facilitate the development of pathways to impact and build a monitoring process to constantly capture and