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PhD Student / Postdoctoral Researcher (gn*) Molecular Biology Reference Number: 10836 Fixed term of 3 years | Full- or Part-Time (65% or 100%) | Salary Grade TV-L E13 | Centre of Reproductive
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with animal models, transcriptomics (long read, single cell), multi-parameter flow cytometry, molecular biology and fluorescence imaging will be preferred. We offer an interdisciplinary research team
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. Experience in working with animal models, transcriptomics (long read, single cell), multi-parameter flow cytometry, molecular biology and fluorescence imaging will be preferred. We offer an interdisciplinary
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of heart disease Your studies will take advantage of in vitro and in vivo pre-clinical models, including hiPSC-derived systems The postdoctoral project will combine experimental (wet-lab) and computational
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, extension is sought) Contract:TV-L Your tasks Molecular laboratory work with 2D and 3D cell culture models Experimental design, data analysis and interpretation Publishing research findings in peer-reviewed
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Postdoc position: mechanisms of autoimmunity & autoinflammation in inborn errors of immunity (m/f/d)
of the immune dysregulation and clinical translation. The Boztug lab is focusing on the discovery of inborn errors of immunity (IEI) and the dissection of their underlying molecular pathomechanisms. The ultimate
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of in vitro and in vivo pre-clinical models, including hiPSC-derived systems The postdoctoral project will combine experimental (wet-lab) and computational (dry lab) approaches Be part of Geman Center
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considered. The ideal candidate will have a background in immunology, tissue biology or cellular metabolism. Experience in working with animal models, cell isolations from tissues (lung, intestine), human
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investigating the molecular mechanisms of aging and the occurrence of age-related diseases. Our aim is to create the basis for new approaches in medicine as a way to improve the health of the elderly (www.leibniz
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to generate reproducible, micrometer-scale controllable, and cost-efficient disease models by bringing together experts in molecular systems engineering, machine learning, biomedicine, and disease modeling