13 computer-science-image-processing "https:" positions at Centre for Genomic Regulation in Spain
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. We combine molecular biology, imaging, genomics, and computational approaches to address fundamental questions in genome regulation. The lab fosters a collaborative and interdisciplinary environment
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mechanisms and genetic drift. The Evolutionary Processes Modeling lab was established in October 2018 and is part of the “Computational Biology and Health Genomics” program at the CRG. Further information can
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these questions, we develop mathematical and computational approaches to estimate mutation probabilities and selection. Tumor mutations are caused by diverse mutational processes, which can be identified through
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quality. Who would we like to hire Must Have Have basic laboratory experience (not important in which field) Be passionate about science, discovery and its process Be a team player and show respect toward
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evolution of cellular structures, with a particular focus on centrioles, centrosomes, cilia, and cytoskeletal organisation. The lab combines cell biology, advanced microscopy, quantitative image analysis
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bioinformatics, genomics, microbiology, computational biology, or related fields • Experience in metagenomics, ideally environmental metagenomics • Genuine interest in environmental metagenomics and microbial
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Core Technologies Programme that includes the technology units of proteomics, bioinformatics, protein technologies, tissue engineering, flow cytometry and advanced light microscopy. The programme is
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using a combination of single cell genomics, genetic screens, and computational biology. We strive to develop novel genomic and bioinformatic tools to answer longstanding questions in the field. We cover
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genomics bench science expert. Blood formation is an essential, biomedically highly relevant, and complex process of cellular differentiation. Our group works on basic science projects on gene regulation in
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(longitudinal behavioural analysis, population-based analysis in neuronal networks, gene expression patterns). We take advantage of computer modelling and bioinformatics analysis (gene networks, neuronal network