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analysis as well as bioinformatic analysis of microbial communities. Qualifications: The candidate should hold an MSc degree in biology, ecology, microbiology, plant pathology, or a related subject
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cells from different mouse models with accelerated aging phenotype. The work of the PhD candidate will include data mining and integration of these datasets with resulting identification of candidate
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of rejuvenation strategies. We have established a large dataset of single cell whole transcriptomic analysis of hematopoietic progenitors and bulk RNAseq of endothelial cells from different mouse models with
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enzyme engineering. The PhD project will involve bioinformatic selection of candidate enzymes, employing a combination of ‘off-the-shelf’ tools based on both sequence and structure. These enzymes will be
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(or equivalent) in biology, bioinformatics, genetics, molecular ecology, or a related field. Solid knowledge and practical experience in molecular ecology, population genetics, and statistical and bioinformatic
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and field conditions. The practical work also includes culturing oomycetes and plants, sampling for molecular and microbiome analysis as well as bioinformatic analysis of microbial communities
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similarities (such as parallel micro-ridges), but also clear differences (such as presence or absence of trichomes or nectar glands on the surface). This interdisciplinary PhD project investigates (1
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nitrogen deposition on a beech forest alters richness and functional diversity of understory vegetation and forest microbiomes (including both phyllosphere and rhizosphere). Can we observe a difference
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machinery) to conduct new catalytic tasks through a combination of chemical intuition and enzyme engineering. The PhD project will involve bioinformatic selection of candidate enzymes, employing a combination
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mimicked with in vivo models of metastasis, which provides unique opportunities to mechanistically dissect what drives the different cell states. You will link clinically relevant phenotypes to putative