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Field
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a set confidence level, typically 90% probability of detection. This project aims to take a radically different approach and integrate the array images with structural integrity assessment to predict
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analyze imaging (DHM) and sequencing datasets (RNA-seq, Ribo-seq where relevant; nanopore long-read). • Perform computational analysis: differential expression, splicing, RNA processing and modification
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the imaging system for generating image datasets from agricultural machines Develop and implement computer vision algorithms for plant disease detection and health estimation in soybeans Design and
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investigates the molecular mechanisms that govern plant development, with a particular focus on symmetry breaking processes in tomato flowers. Symmetry breaking is a fundamental biological phenomenon in which
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imaging to further define the substrate spectrum of SPPL3 (Hobohm et al . (2022), Cell Mol Life Sci; Truberg et al . (2022), BBA Mol Cell Res; Brauer et al . (2024), EMBO J). Moreover, many independent
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the Clinic for Radiology. As one of Germany's leading university radiology departments, we provide all outpatients and inpatients at UKM with state-of-the-art diagnostic imaging and image-guided therapy
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imaging techniques Experience with basic statistical approaches Motivation to work in an international research environment Motivation to learn systems biology approaches, high-throughput methodologies, and
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relate to processing-relevant traits such as fry quality, yield, and waste? The project will take an integrated approach combining advanced imaging, quantitative phenotyping, and genetics. A high
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• Integration of physiological and biochemical data with advanced phenotyping approaches (e.g. ther-mal imaging) • Statistical analysis and interpretation of multi-factorial datasets • Active collaboration with
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sustainable machine learning approaches and addressing renewable energy related projects. Likewise, deploying a novel paradigm of KGML (knowledge guided machine learning) can propel further research. PhD