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include but are not limited to: network architecture design for NTN and terrestrial network (TN) convergence, intelligent traffic steering algorithms between TN and NTN, orchestration of TN/NTN resources
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Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing techniques to enable large-scale data search
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foundational understanding of children's agency in digital environments increasingly dominated by AI systems. The UCL team is specifically focusing on the educational technology angle, developing agency
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research in fundamental & applied AI that is directly relevant to policy. to develop and deliver expert-led training on AI to civil servants across government. Fellows will spend 50% of their time on each
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are not limited to: network architecture design for NTN and terrestrial network (TN) convergence, intelligent traffic steering algorithms between TN and NTN, orchestration of TN/NTN resources for end-to-end
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development of future proposals for funding, into AI for renewable energy. You will consider ways in which the integration of machine learning algorithms might support the wider integration of, and uptake
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Search over Personal Repositories - Secure and Sovereign”). The post is based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating
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. In this role, you will be part of the research team, working to develop and evaluate privacy-preserved Generative AI algorithms for generating synthetic Personal Identity Information (PII). This aims
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, operations research, and management science, developing rigorous and practical methods for algorithmic risk assessment. You will become part of the broader AI2 collaboration, involving leading researchers from
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combining these to explore the possibility of improving outcomes. These algorithms will then be used to develop a prognosis platform. You will investigate different approaches and find novel ways to improve