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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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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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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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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
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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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-oriented research. The work will be carried out in the new OpenIreland research infrastructure, a large-scale testbed for experimentation in open optical, wireless and cloud technologies. The position will
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of AIS's existing cloud-based 'pipelines' product, which allows sporting practitioners to develop computer vision (CV) applications in a no-code environment.
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build the sustainable companies and societies of the future. The EISLAB division of the Department of Computer Science, Electrical and Space Engineering conducts research within Cyber-Physical Systems
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(NOₓ), and contrail-induced cirrus cloud formation. Aviation currently accounts for approximately 3.5% of total anthropogenic radiative forcing, with non-CO2 effects responsible for around two-thirds