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produced from steam methane reformation of natural gas, which is an efficient and mature technology, yet it requires high temperatures and has a large carbon footprint. This PhD project addresses a key
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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
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, or computational strategies to your interests—whether that involves large-scale reservoir simulation, pore-scale physics or supercritical CO2 behaviour. The project will be developed within a vibrant research