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Institute, MI), Professor Simon Leedham (NDM), Dr Joshua Moore (MI) and Dr Eoghan Mulholland (NDM). You will be responsible for adapting existing mathematical and statistical methods for analysis of high
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, including Spatial Transcriptomics and Multiplex Immunofluorescence platforms, for validation and calibration of mathematical models. You will also develop skills in mathematical modelling and spatial analysis
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an available option. Applicants with a range of academic subject backgrounds are welcomed, including natural sciences, epidemiology, engineering, statistics and applied mathematics with experience and
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available option. Applicants with a range of academic subject backgrounds are welcomed, including natural sciences, engineering, statistics and applied mathematics with experience and/or growing interest in
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analysis and is increasingly used in cancer research to uncover morphological features linked to disease pathology and severity. Similarly, molecular profiling through ‘omics technologies has provided new
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developing mathematical algorithms and simulations in MATLAB, in particular with Semidefinite Programming and Sum of Squares and of the analysis and design of feedback control systems using these approaches
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base, the partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will
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. The project will also involve close collaboration with researchers from other disciplines within the Oxford Martin Circular Battery Economies Programme, who are working on second-life battery analysis, re
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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