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for high-dimensional datasets, including spatial bulk and single-cell RNA sequencing, mass and flow cytometry, and imaging data derived from both patient samples and experimental models. The overarching aim
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CANDIDATES ONLY About Us The applicant will join the Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. We are a highly collaborative
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into the regulation and function of diverse cellular processes. To this end, we use Vaccinia virus as a model together with quantitative imaging and biochemical approaches to study a variety of cellular processes
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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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against undesirable behaviours in Large Language Models (LLMs) and Text-to-Image Diffusion Models (T2Is) towards reliable and responsible human-centred AI systems. NeSyDebates aims to focus on requirements
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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
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to help prevent, diagnose and treat illnesses such as cancer, heart disease, infectious diseases and neurodegenerative conditions. The Crick is a place for collaboration, innovation and exploration across
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managing and converting between file formats Experience with spatial data analysis tools/platforms (e.g.: napari) Programming skills working with image data in Python Experience with metadata, data