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, stable isotope tracers, medical imaging). Experience with molecular biology techniques, stable isotope tracers methodologies, GCMS desirable. -Familiarity with bioinformatics and computational biology
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responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal
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to convert CO2 into valuable bioproducts, advancing sustainable bioeconomy. It heralds a paradigm shift on sustainable production of chemical compounds, food and materials to displace fossil fuels
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responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal
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experience of the laboratory delivery of multiplex imaging datasets of tissue samples as well as significant laboratory experience of general methods including immunoassays and cell culture. You will have
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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
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techniques, multispectral flow cytometry, and bioinformatic analysis of transcriptomic (RNAseq) datasets. Experience with image analysis, particularly for immunofluorescence, is desirable. You should be
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models of spillover infection and transmission of prototype viruses representing viral families concern to support the development of methods for virus sequence analysis and inference of human transmission
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, based on a range of settings and scenarios of navigation in closed environments; these should detect obstacles and detect/characterise branches (e.g. holes, tunnels, stairways). Implement prototype
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the Medical Research Council and Medical and Life Sciences Translational Fund. It offers an exciting opportunity to work in a vibrant multi-disciplinary team that crosses the domains of clinical imaging and