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Predictive and optimization-based control of smart grids: theory and algorithms School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr P Trodden Application Deadline
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Modern technology is dependent on effective distribution of time and frequency signals, with different end users requiring different levels of accuracy and reliability. The technologies used
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PhD Studentship: Open Radio Access Network (ORAN) for Distributed Edge Computing Orchestration in 6G
://cheddarhub.org The work is envisioned to have great impact on design and development of intelligent AI/ML orchestration algorithms in real 6G experimentation test beds. The applicant is envisioned to further
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of the advertised post are to contribute to the BPAI project (as described below), with emphasis on probabilistic verification or programming for concurrency or distribution. This may involve probabilistic session
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intelligent and highly distributed systems with the use of advanced AI/ML techniques. Research topics include future mobile networks and 6G, AI/ML for network intelligence, edge intelligence, distributed AI
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://cheddarhub.org The work is envisioned to have great impact on design and development of intelligent AI/ML orchestration algorithms in real 6G experimentation test beds. The applicant is envisioned to further
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Status, distribution, and dynamics of marine biodiversity School of Biosciences PhD Research Project Self Funded Dr T Webb Application Deadline: Applications accepted all year round Details Marine
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PhD Studentship: Accelerating Statistical Algorithms through Machine Learning Award Summary 100% home fees covered, and a minimum tax-free annual living allowance of £19,237 (2024/25 UKRI rate
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Nonlinear Distributed Control School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Pablo Baldivieso Monasterios Application Deadline: Applications accepted all year
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developing new methods and techniques that will improve standard ML algorithms so as to achieve good performance outside their training distribution, by treating high-dimensional problems as an explicit