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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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We are seeking a full-time Postdoctoral Research Assistant to join a cross disciplinary research project to improve our understanding of colorectal cancer. Deep learning has revolutionised image
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exploring B cell migration in the spleen. The successful candidate will have extensive experience in handling and processing live spleens and an established expertise in live imaging of this organ. As a
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with cutting-edge models and technologies—including patient-derived glioblastoma organoids, CRISPR-based screens, mass cytometry, and advanced microscopy—to dissect these complex biological processes
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migration, nanoscale assembly, or complex charge-screening processes are still poorly understood despite their critical impact on electronic properties and device performance. The project will provide a
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biological, and live cell fluorescence imaging experiments. Associated structural analysis of the proteins by cryo-electron microscopy will be undertaken via collaboration with other workers. This full-time
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collaboration with the Translational Gastroenterology Unit (TGU) and the Ludwig Institute of Cancer Research (LICR) we aim to develop a computer guided endoscopy image recognition system that will support
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group aims to determine regulatory pathways affected by disease by implementing the use of spatial proteomics combined with transcriptomics and live imaging. The total proteome of a neuron includes a vast
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of RNAseq data and in vivo modelling of cancer. In addition to leading your own research, you will provide guidance and support to junior members of the lab, including PhD and project students, research
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to target specific transcription factors (iii) use of high content imaging and AI to phenotype these cultures (iii) use of bulk and single-cell RNAseq to characterise the transcriptional profile of each cell