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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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At the University of Vienna more than 10,000 personalities work together towards answering the big questions of the future. Around 7,500 of them do research and teaching, around 2,900 work in
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At the University of Vienna more than 10,000 personalities work together towards answering the big questions of the future. Around 7,500 of them do research and teaching, around 2,900 work in
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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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Cluster of Excellence quantA. The group’s research combines the development of scalable photonic quantum technology for quantum computing and other quantum information applications with the investigation
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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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clustering of landslides across different scales (4) often triggered by earthquakes or intense rainfall events (3,5). These findings demonstrate that the rates and pattern of landsliding change through time
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intensity of these changes. This PhD project will ultimately enable aircraft to reroute safely and efficiently in real time as weather evolves. By merging scientific machine learning, large-scale data
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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