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-related traits, and heterosis. In the era of large population size and dense genomic data such as whole-genome sequencing, new algorithms are needed to remove the bottleneck of computational load for such a
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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Develop solutions to integrate large foundation models
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large environmental and ecological data sets, incl. empirical, remote-sensing and simulated model data knowledge in programming languages (UNIX, C, or similar) and script-based programming (R, Python
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of detailed electrical data and optical emission information. Cathodoluminescence measurements. Since degradation experiments typically extend over one week or longer, all measurements are performed in a fully
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Pathogens, a WHO Collaborating Centre, and a member of the Leibniz Research Association. The Computational Infection Biology Department, led by Thomas Otto, is seeking a highly motivated PhD Student (in data
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mining. In-depth knowledge of the design, analysis and implementation of algorithms for large text corpora, including efficient data pipelines and clean experimental design. Strong NLP skills for semantic
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these, Nucleotide-binding, Leucine-rich-Repeat proteins (NLRs) constitute a large family of intracellular receptors of pathogen-associated molecules, termed effectors. To restrict infection, NLRs trigger a response
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of large data sets Familiarity with genome quality assessment, contamination screening, and troubleshooting of sequencing datasets Familiarity with phylogenomic pipelines and comparative genomics workflows