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essential to determine how these models can be made lightweight in terms of computational complexity, memory footprint, and energy consumption for deployment on edge devices or constrained gateways
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-driven approaches to health, society, and policy. BISI combines expertise in epidemiology, biostatistics, health economics, and machine learning to tackle complex societal challenges. BISI is actively
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). Experience in biosignal analysis or wearable devices is desirable. To apply please contact the supervisors; Dr Pengpeng Hu - pengpeng.hu@manchester.ac.uk and Prof Li - henry.yili@manchester.ac.uk . Please
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ambitious research team exploring quantum phenomena in large scale and complex systems, from high-temperature Bose-Einstein condensates to trapped solid-state particles in ultra-high vacuum. We combine
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implementation of complex systems. We focus on ensuring that our research results contribute to creating a better society by supporting areas such as health, green transition, energy supply, and life science. We