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. Your work will focus on identifying the mathematical knowledge and properties to guide hardware optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g
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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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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
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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
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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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) in the 5' untranslated region (5'UTR) of HIV-1. Although pro- and antiviral effects have been described, its exact role in the different RNA isoforms remains poorly understood, as short read sequencing
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 18 days ago
) Basic knowledge on genomic and transcriptomic analysis, as well as bioinformatic tools relevant for the project; e) Previous experience in supervising Master students. 7. Evaluation of the applications
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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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-driven and passionate about fundamental research in the context of evolutionary biology and ecology. Has strong bioinformatic skills (python, ideally experience with methylation data). Has strong
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consumers. You'll gain deep interdisciplinary experience—combining multiple data layers and approaches including bioinformatics, machine learning, food safety management, regulatory science, genomics and user