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EU MSCA doctoral (PhD) position in Materials Engineering with focus on mechanistic study of high cor
English. Additional qualifications: It is advantageous to have experience in one or more of the following areas: Electron microscopy (environmental TEM and SEM) Large data image treatment Corrosion
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, and regulate plasticity. We use cutting-edge methods (multi-omics, single cell, live cell imaging, modelling, chromatin biochemistry as well as various developmental, stem cell, and cell biology systems
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professor, one assistant professor, one postdoc, and a large number of PhD students. The project includes strong partnerships with the University of Leipzig (Bioinformatics, Prof. Peter Stadler
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, novel high-resolution imaging systems to investigate submillimeter-scale turbulent dynamics in multiphase environments such as the ocean surface. The project is part of the Collaborative Research Centre
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PhD fellowship at the Copenhagen Center for Glycocalyx Research at the Department of Cellular and Mo
leader in the field of membrane biology and glycosciences. We are composed of several research groups and host about 20 postdocs and 20 PhD students, in addition to master’s students and guest researchers
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flow cytometry Immunohistological staining and imaging of tissue sections using multiplexed immunohistochemistry Biochemical assays for cytokines and other inflammatory mediators Cell culture experiments
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organoids, single cell multiomics, live cell imaging, and animal models. Tasks: to actively pursue the PhD project with the aim of characterizing the molecular and functional mechanisms of epithelial
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after damage. The applied techniques will include e.g. mouse and human kidney organoids, single cell analyses, proteomics, metabolomics, live cell imaging, and animal models. Tasks: to actively pursue
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epithelial cells and neurons in the intestine. The applied techniques will include molecular and cellular biology methods (e.g. neuroepithelial co-cultures, organoid cultures), advanced imaging (e.g
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principles that regulate host-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine learning tools. A specific focus will be put