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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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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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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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. 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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Experience with machine learning algorithms and ideally experience developing novel methods Understanding of basic biological principles and experience interpreting ‘omics data Ability to analyse information
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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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the presence of interference in a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide enhanced interference resilience against different interfering systems. Develop, with
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model checkers; proofs of safety and/or security properties; programming languages and/or type systems; concurrent and/or distributed algorithms; and related topics. The successful applicant will work in