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Field
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learning and machine learning for biological data Sequence and structure analysis of large-scale datasets Functional annotation and evolutionary analysis Collaborative research with experimental virology
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leading the establishment of a centralized repository for genomic data and metadata, with a strong emphasis on existing and novel methods for the evaluation of genome quality, indexing and clustering
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electron microscopy design and implement deep learning models to enhance resolution of large field-of-view imaging techniques integrate imaging data across modalities for improved spatial resolution and
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nano-computed tomography, and scanning electron microscopy design and implement deep learning models to enhance resolution of large field-of-view imaging techniques integrate imaging data across
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provide large and complex datasets. By applying advanced pattern recognition and clustering algorithms, the aim is to automatically detect coherent spatial domains. These domains represent regions with
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. Knowledge Graphs based on engine propeller combinator diagrams of the same vessels. Machine learning algorithms for data clustering and regressions of ship performance and navigation data sets as a part of
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vessels and ship systems. Knowledge Graphs based on engine propeller combinator diagrams of the same vessels. Machine learning algorithms for data clustering and regressions of ship performance and
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Optics, Quantum Nanophysics and Quantum Information group of the Faculty of Physics. We are member of the Vienna Center for Quantum Science and Technology (VCQ), one of the largest quantum hubs in Europe
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Course location Karlsruhe Description/content The Cluster of Excellence 3D Matter Made to Order (3DMM2O) is a Research Cluster jointly run by Karlsruhe Institute of Technology (KIT) and Heidelberg
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the companies at Odense Havn and similar partners making large structures across Denmark and Europe. LSP is integrated with the Odense Robotics Cluster involving startups and established companies in robotics