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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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, 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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. 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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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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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
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, to develop a novel end-to-end neuromorphic design approach based on spiking neural networks (SNNs). The project aims to develop novel computing solutions for the defence and security sector, that can
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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
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We seek to recruit a Research Associate/Fellow to join our team developing a groundbreaking technique based on autofluorescence (AF) imaging and Raman spectroscopy for detection of positive lymph
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, to develop a novel end-to-end neuromorphic design approach based on spiking neural networks (SNNs). The project aims to develop novel computing solutions for the defence and security sector, that can