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familiar with marine ecosystems, the deep biosphere or marine microbiomes and the necessary bioinformatic and statistical analyses of such data (e.g. taxonomic assignments, gene prediction, phylogenetics
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glaciology, remote sensing observations, and basic geoscience analysis. It would be an advantage if the candidate has experience working with statistical techniques for large scale datasets and GNSS data but
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collaboration, organizational, and communication skills. Experience with statistical techniques, paleoclimate reconstruction methods, and dating methods is an advantage. Meet your new colleagues You will join the
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sequencing and library preparation, molecular biology, organoid culture). However, interest for or previous experience with single cell data analysis and statistical modeling are more than appreciated. Formal
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applications Experience in managing data and model simulation Insight into applied statistics and spatial data Experience with collaborative data project infrastructure Who we are At the Department
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-specific T cells Multicolor flow cytometry Apply analytical and statistical tools to identify patterns in large datasets The candidate should demonstrate evidence of self-driven and independent research
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microbiomes and the necessary bioinformatic and statistical analyses of such data (e.g. taxonomic assignments, gene prediction, phylogenetics). Our department places a high value on cross-disciplinary and cross
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Python, including statistical analysis, visualization, and multi-omics data handling in collaboration with the team. Collaborating within an interdisciplinary team, including potential teaching or
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-specific T cells Multicolor flow cytometry Apply analytical and statistical tools to identify patterns in large datasets The candidate should demonstrate evidence of self-driven and independent research
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in bioinformatics and big data statistics Research experience in areas such as experimental work involving soil and plants, both in the field and in greenhouses Further, we will prefer candidates with