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Models”, led by Prof. Jonathan Brewer (Department of Biochemistry and Molecular Biology, SDU), Dr. Mike Barnkob and Prof. Torben Barington (Department of Clinical Immunology, Odense University Hospital
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Job Description The Department of Molecular Medicine (IMM) at the University of Southern Denmark (SDU) invites applications for a fully funded postdoctoral position in aging biology, based in
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laboratory at the Department of Molecular Biology and Genetics invites you to apply for a one-year Postdoc position. Expected start date and duration of employment This is a one-year position starting from 1
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-Integrated 3D Skin Models”, led by Prof. Jonathan Brewer (Department of Biochemistry and Molecular Biology, SDU), Dr. Mike Barnkob and Prof. Torben Barington (Department of Clinical Immunology, Odense
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cutting-edge experimental and computational technologies. Our aim is to dissect dynamics and cellular programmes active during human blood lineage development and to decipher how haematopoietic
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for Food Allergy at DTU National Food Institute, you will be part of a dynamic and highly ambitious research and innovative environment, with many national and international collaborators from both academia
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characterisation of molecular building blocks and templates; enzymatic synthesis and analysis of dynamic systems of oligosaccharides; biophysical studies using spectroscopy (NMR, UV-Vis, fluorescence and CD
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molecules. The project is based in the team of professor Gregers Rom Andersen at the department of Molecular Biology and Genetics (MBG). Funding for the project is secured by a major grant from the Novo
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Two year postdoc position at Aarhus University for single molecule FRET based investigations of l...
molecules. The project is based in the team of professor Gregers Rom Andersen at the department of Molecular Biology and Genetics (MBG). Funding for the project is secured by a major grant from the Novo
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and 10X multiome data sets to reveal the molecular programmes that are active in human blood cells. You will employ cutting-edge single-cell computational approaches to chart and understand the gene