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. Robust reservoir-scale modelling is therefore essential for predicting system performance and informing design and operational decisions. Leveraging geological, hydrological, and thermal models developed
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support massive Internet-of-Things (IoT) deployments through technologies such as network slicing. At the same time, the emergence of large-scale quantum computing poses a significant threat to current
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(Edge AI) enables deploying AI algorithms and models directly on edge devices. However, AI workloads demand high performance processing, large scale data handling, and specialized hardware accelerators
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an efficient and mature technology, yet it requires high temperatures and has a large carbon footprint. This PhD project addresses a key challenge: efficiently producing bio-methanol from abundant
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acoustic data, has shown transformative potential in domains such as healthcare, environmental monitoring, and autonomous systems. However, most advances rely on large datasets and computationally intensive