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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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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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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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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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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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DoS: Professor Sarah Boulton 2nd Supervisor: Dr Martin Stokes 3rd Supervisor: Dr Michael Whitworth, AECOM 4th Supervisor: Dr Joshua Jones, AECOM Applications are invited for a 3.5 years PhD
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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