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This PhD project focuses on strengthening network security for large-scale distributed AI training. As training increasingly spans multiple data centers connected over wide-area networks, it
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format. This will allow combinations of neural networks with physics models. The project brings together PhD students and senior researchers from multiple disciplines to tackle challenges in sustainable
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! Education Master's degree (Bac+5) in telecommunications, computer science, or a related field, with an interest in AI, cognitive networks, or connected vehicles. Experience and skills Prior experience with
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the evidence–base needed to understand the impact on health, to inform public policy, and to develop potential mitigation strategies. Traditionally, this information has come from ground monitoring networks
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As Austria's largest research and technology organisation for applied research, we have set ourselves the goal of making substantial contributions to solving the major challenges of our time
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, Austria, and with Chrometra, a Belgian company. By being embedded in the WATER research network, you will also interact with parter groups located across multiple EU research groups, building your research
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environments—such as fleets with multiple aircraft types. Objectives Objective 1: Map current data types, structures, and interoperability challenges to build a detailed "as-is" understanding of current
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. TUD has established the Collaborative
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: this provides capability for accurate and fast modelling of urban drainage, handling the full complexity of flow paths on impermeable surfaces, green space, buildings, pipe networks and BGI features
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optimising performance across multiple timescales and spatial domains. Systematically resolving these challenges in renewable-dominated power networks stands as a critical cornerstone for enabling the roadmap