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, distribution system operators (DSOs), households and other stakeholders. Effective planning depends on the ability to share and combine data from diverse sources, including building characteristics, energy
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transition depends on data that almost no one is allowed to see. Distribution system operators (DSOs), municipalities and energy communities need high-resolution grid and consumption data to plan grid
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depend closely on sea ice and under‑ice habitats, while salps thrive in warmer, often ice‑free waters. Warming and sea‑ice loss are already shifting their distributions and increasing spatial overlap, with
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passionate about building an entanglement-based quantum internet? In this PhD project, you will design an entanglement source, a routing architecture, protocols, and set up a testbed that distributes and
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transition depends on data that almost no one is allowed to see. Distribution system operators (DSOs), municipalities and energy communities need high-resolution grid and consumption data to plan grid
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distribution (QKD), where you will adapt both the codes and their decoders to the specific security and performance requirements of QKD protocols. Beyond QKD, you are encouraged to explore open problems in
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and trace elements distribute between molten steel, slag, and vapor under next-generation steelmaking conditions. The research will focus on experimentally determining equilibrium partitioning behavior
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further climate change. At the same time, climate action entails distributional effects and can exacerbate existing inequalities and impact the lives of citizens. This manifests itself in concerns regarding
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interfaces to share intermediate data for distributed training and processing, generating large traffic flows. Low and deterministic latency will be required for specific application in data centre for AI
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a range of directions, including distributed MIMO and angular diversity. In this work, you will examine several trade-offs involved in scaling detector arrays, including bandwidth limitations