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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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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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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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bacterial fitness Analyse the formation of clusters among bacteria using fluorescence microscopy Investigate bacteria on a single-cell level using microfluidics and flow-cytometry Quantify the amino acids
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offered provide access to challenging and interdisciplinary projects integrated into large national and European research consortia such as the DAPHNE (DAta for PHoton and Neutron Experiments) NFDI
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simulation workload and update the solver data structures when the mesh changes. These approaches would be applied on modern large-scale heterogeneous parallel computing environments where both CPUs and GPUs
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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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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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and interdisciplinary projects integrated into large national and European research consortia such as the DAPHNE (DAta for PHoton and Neutron Experiments) NFDI consortium. The group offers well-equipped
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offered provide access to challenging and interdisciplinary projects integrated into large national and European research consortia such as the DAPHNE (DAta for PHoton and Neutron Experiments) NFDI