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, compression, learning, and inference for classical and quantum data exchanged through classical and quantum networks. The objective of the PhD study is to explore and address research and design challenges
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derived use cases by focusing on one or more of the following topics in their PhD project: Training and inference of ML models on GPU clusters. Method development for scalable and green AI. Use cases in
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to the requirements for learning or inference by various AI modules deployed in the devices and the network. This line of work will investigate the fundamental tradeoffs among latency, accuracy, and energy efficiency
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expression and developability. Propose and validate optimization tools for performing (Bayesian) design of experiments. System validation and iterative refinement based on empirical data. Test and refine
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). Footage will be collected using various underwater cameras deployed near the seabed. The sampling methodology is considered non-invasive because no fish is harmed, and the sampling infers almost