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microbial activity (e.g. stable isotope tracing), or in genome/-omics analysis is advantageous, but not required. Bioinformatics skills such as working knowledge of R and scripting languages, as well as a
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chem- and bioinformatics to computer vision and social network analysis. Machine learning with graphs aims at exploiting the potential of the growing amount of structured data in all these areas
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portfolio. The successful candidate will work with interdisciplinary teams (clinical, analytical, and bioinformatic scientists), apply shotgun lipidomics and related analysis to various fields, and streamline
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: Molecular biology, developmental biology, bioinformatics techniques (e.g., qualitative and quantitative gene expression analysis, transcriptomics). Morphological and imaging approaches (e.g., confocal