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experiments, molecular cloning, cell culture, and standard laboratory methods such as flow cytometry and RT-qPCR. The computational work includes, for example, the analysis of omics data and computational
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fluids, flow-induced pattern formation in both simple and complex flows (e.g. flow instabilities, product defects), multiscale analysis, and the application of machine learning techniques. About the
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include technique development work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow
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work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you
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also include technique development work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a
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processes. A demonstrated interest in data visualization and large-scale data analysis is highly desirable. The ideal candidate will have a keen interest in understanding complex biological systems
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activities aimed at developing and using biomarker analysis in blood samples for next generation cancer diagnostics. The work will also include studies in basic tumor biology, where we use various in vitro
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and Data Science for Spatial Genomics in Diabetes This position centers on the development and application of machine learning, image analysis, and integrative omics approaches to spatial
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. Importance will also be placed on experience of qualitative methods for data collection and analysis. Given the character of the research project importance will also be placed on good knowledge of both
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motor behavior analysis. Technical experience with imaging, molecular biology, immunohistochemistry, in situ hybridization are also highly valued. Technical experience with embryo electroporation and /or