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, we are investigating the mechanical cues regulating the partition and migration of body axis progenitors. We have developed innovative techniques such as tissue force microscope (TiFM) enabling in vivo
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processes associated with CIN [1], leveraging single-cell DNA sequencing understand CIN heterogeneity [2], and development and implementation of machine learning and AI models to imaging data [3]. The student
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transcriptomics and histone mark profiling as well as by live imaging approaches. As part of this project, you will have the opportunity to gain computational data analysis skills. This studentship comes with
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: Advanced molecular and protein analysis Mass spectrometry-based imaging Multi-omics technologies Preclinical cardiometabolic animal models They will also gain professional development in data stewardship
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metabolomics, as well as imaging mass cytometry, and test the effect of AZ clinical compounds on the immune-metabolic landscape of our PanIN-to-PDAC models. Dr Koulman will provide training and support with
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combustion experiments and in particular hydrogen and liquid fuels, image processing, and excellent knowledge of turbulent combustion. Appointment at Research Associate level is dependent on having a PhD
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to symmetry breaks in the patterning process. A hybrid modelling approach integrating the dynamics of a core network while utilising a virtual template from experiments for cellular growth and division will be