70 distributed-algorithms-"Meta"-"Meta"-"Meta" Fellowship positions in United Kingdom
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to) fundamental research in machine learning or statistics, algorithm design, the application of AI methods in science, healthcare, social sciences, or business. You should have a PhD or equivalent level of
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electrical power distribution system. Prior knowledge on power system condition monitoring would be an advantage. Experience in project work would an advantage. Share this job Facebook Twitter LinkedIn Apply
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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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welcome applications from passionate, skilled, and committed individuals. About the Role The spatial distribution of schistosomiasis coincides with development of certain water management infrastructure
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affordability, welfare, and income distribution. Contribute to the preparation of policy briefings, academic publications, and public-facing reports. Present findings in academic and policy settings, including
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The 6G National Research Programme is at the forefront of pioneering research and development in the field of 6G technologies. As part of the Communications Hub for Empowering Distributed Cloud
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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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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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behind this efficiency by developing a general model of wing mechanosensing, revealing how sensor distribution and morphology have co-evolved with flight dynamics. The successful applicant will: Measure
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of schistosomiasis across rural-to-urban settings and develop tools to support targeted interventions. A key focus will be on mapping snail vector distribution near expanding water infrastructure (e.g., sand dams) in