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is a willingness to work collaboratively with the wider team. If you like the idea of working as part of an interdisciplinary team that is helping bring cloud computing to the world of genetics-based
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and Master’s students in Informatics and Data Science. Supervise Bachelor’s and Master’s theses. We Offer Practice-oriented research projects with leading academic and industry partners (like Google
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the understanding of large-scale irrigation-atmosphere interactions. You will use state-of-the-art global satellite remote-sensing data to analyse the impact of irrigation on cloud and rain formation. This will
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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such as landslide movement style, runout, and how landslide hazards evolve over time. This Ph.D. project will leverage the analysis of new time-series data from cloud-based satellite image archives
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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. The research should focus on low-power embedded systems, multimodal sensing (including wearable shoe-based platforms), and edge-cloud computing with serverless and federated learning techniques. You will work
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team of researchers on a European project. As a main topic, you will perform your research in one of these areas: -Service oriented software in the cloud-to-edge compute continuum targeting robust
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convection while also capturing the large-scale global circulation. Further into the project, there is the possibility to work with moisture or cloud tracking algorithms, regional models, and validation with
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with, cloud computing and virtualisation technologies Familiarity and hands-on experience with machine learning techniques desirable Desirable to have work experience (through internships or similar) in