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Field
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to process and understand large experimental datasets (e.g., image processing) #analyzing experimental results; developing conceptual models and parameterizations #scientific publication and presentation
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key role in gene regulation. By employing omics-based approaches, metabolite tracing, proximity-labelling, and advanced imaging techniques, this project offers a unique opportunity to: Explore how
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Soil BON monitoring network, controlled experiments, and modelling. Your role will be pivotal in developing data infrastructure and automating data and image exchange processes. You will collaborate with
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the Collaborative Research Centre 1340 ‘Matrix in Vision’, glycosaminoglycans (GAGs) and their complexation to cationic imaging probes are investigated using a range of different techniques. The position to be filled
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, and image analysis tools and working on a computing cluster (HPC). Vivid Interest in interdisciplinary research, leading and working on projects with pathologists, medical experts, computer scientists
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Funded by the German Research Foundation (DFG), Research Unit 5339 "AI-based Methodology for the Fast Maturation of Immature Manufacturing Processes" was established in 2023 at KIT and the
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Learning Graph Neural Networks Time series analysis Diffusion models Large Language Models Applications in health and medicine-related topics, e.g. medical text, tabular data and image processing, infection
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to develop a monitoring box that can be used at the ocean surface. In addition to the hardware, methods will be developed to capture and process sensor and image data (AI for phytoplankton). Qualification
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at a German university Profound knowledge of C++ /Python Experience with ROS Background in neural networks for image or point cloud processing Analytical mindset and experience in algorithm development
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surveillance, ensuring optimal image clarity is crucial. Traffic signs, with their standardized design and critical importance for navigation, are ideal reference points for this process. What you bring