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flow behaviors that existing correlations and turbulence models fail to predict. Understanding and modeling these effects is crucial for industrial applications such as gas-turbine internal cooling
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being part of these two networks. Subject description The project involves mathematical modelling of complex fluid dynamics, in particular viscoelastic flows in nano-structures. The work involves
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of this position is within the field of immuno-oncology, specifically establishing ovarian cancer tumor models based on cell lines and freshly resected patient tumor material for evaluation of immunotherapeutic
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three years before the application deadline. Experience with the following in vivo experimental studies: handling and breeding genetically modified mouse models, including diet-induced obesity models
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senior researchers and doctoral students. Current research areas within the Department of Mathematical Statistics include stochastic models, statistical theory and computational statistics, probability
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that underlie acute complications such as heart attacks and strokes. The research is translational and includes studies of human tissue and several in-vitro models. The group has for many years been
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interfacial rheology and microfluidics. At the beginning model polymeric particles will be used, such as microgels. With these experiments we will study how the individual particle properties such as softnes
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. Teaching skills. Additional assessment criteria: Particular weight will be given to a candidate’s research background and and expertise, and its match to the scientific needs of the project. Consideration
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responsibilities The candidate will use human mesenchymal cells to create human in vitro and in vivo models of the bone marrow. The projects consist of establishing relevant bone marrow models and exploit them
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solution that has the potential to enhance current immunotherapy approaches. This includes cell culture, microscopy, histology and working with animal models. The work duties also comprise data analysis