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The position is to be filled within the Marie Skłodowska-Curie Doctoral network METAMIC 3 - Metaproteome-based leveraged microbiome management in the context of One Health. METAMIC 3 is funded by the European
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approaches across a range of model organisms to understand how and why we age. As a PhD candidate at FLI, you’ll be part of an international and interdisciplinary environment where basic science meets
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools
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experience growing, managing, and phenotyping plants in the field and greenhouse. You have experience using modern approaches in root phenotyping, image analysis, or simulation modeling to understand
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combines microbial genomics, transcriptomics, and in vitro infection models to explore the adaptive trade-offs between drug resistance and virulence phenotypes. The position is funded for 3 years and
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approaches in root phenotyping, image analysis, or simulation modeling to understand the functional roles of plant roots in agroecosystems. You have excellent communication skills and will to collaborate with
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the field and greenhouse. You have experience using modern approaches in root phenotyping, image analysis, or simulation modeling to understand the functional roles of plant roots in agroecosystems. You have
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microscopy. Root architectural phenotyping. Plant and root physiological measurements to determine the function of root phenotypes. Functional-structural plant modeling to determine the benefit of root
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specimen-based analysis of trace fossils with exploratory fieldwork in southern Namibia, and neoichnological experiments in collaboration with scientists at Senckenberg am Meer in Wilhelmshaven. With
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atmospheric aerosol particles, their interactions with clouds and turbulence, and cloud microphysics. The focus is on both process-based studies and long-term observations, with which we contribute