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Field
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interface that provides operational insights. As the project progresses, you will continuously enhance the ML models to adapt to more sophisticated data, ensuring the tools remain at the cutting edge
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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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teaching at the Chair, in particular with a focus on the planning and design of railroad systems application and continued development of digital planning methods such as Building Information Modeling
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conferences Requirements: a university degree in the field of computer science, data science, computational modeling or related subjects in combination with civil engineering, transport engineering a strong
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an emphasis on in vivo assays, animal models and state-of-the-art imaging tools Soft skills seminars on communication, presentation and other topics equally relevant for achieving success in both a scientific
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and histopathological characterization of tumor cells in tissues using chemical and fluorescence staining Handling in vivo and in vitro models to test research hypothesis and refine study designs
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and histopathological characterization of tumor cells in tissues using chemical and fluorescence staining Handling in vivo and in vitro models to test research hypothesis and refine study designs
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quantum processors using this technological platform design and implement optimization techniques for full-stack improvement of quantum algorithms model major sources of experimental error for control
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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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algorithms model major sources of experimental error for control theory or co-design methods Previous works can be found under the bibliographies of Dr. Felix Motzoi and and Dr. Matthias Müller: https