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to investigate the influence of glucosinolate-based amines on the formation of Maillard-like products in model systems and foods, to isolate and identify the resulting products and to find out whether
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: process multisource satellite and UAV based data collected in the case study regions apply and develop models for tillage mapping and monitoring using remote sensing apply and further develop machine
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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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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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modelling, starting as soon as possible. The position is funded for 36 months. Remuneration is in accordance with the German public tariff scheme (TV-L Brandenburg), salary group E 13. This is a part-time
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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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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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. However, the transcriptional regulation of this process remains is not fully understood due to the complexity of crop plants as models for molecular and imaging studies. This DFG-supported project aims