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learning to improve detection using multiphase CT imaging and longitudinal biomarker data in routine practice. You will work with multidisciplinary clinical and AI teams on applied research, developing and
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this condition. You will evaluate their interactions using in vivo micro-CT, intravital imaging, spatial transcriptomics and molecular analysis techniques, identifying the key pathways governing this process
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About the Role This is an exciting position where applicants are invited to join a multi-disciplinary team of bioengineers, biomedical scientists, and computer scientists working together at Queen
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progression. The Iskratsch Group , at the School of Engineering and Materials Science, Queen Mary University of London is exploiting cutting-edge mechanobiological, as well as imaging approaches2-5 with the aim
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culture models and cell imaging to decipher mechanisms contributing to cancer cell invasion. We offer a vibrant and creative multidisciplinary environment, and the successful candidate will be supported
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Schwann cells, myelination assays, or co-culture systems, and familiarity with advanced imaging or quantitative image analysis will be desirable for the role. About the School/Department/Institute/Project
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parasite mutants, antibodies, spatial proteomics, real-time and super-resolution imaging, we will reveal essential protein domains and characteristics, will identify interacting protein partners and will