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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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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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We are seeking a Research Fellow to perform research on deployment of machine-learned models for health analytics on distributed IoT/edge/cloud systems using transprecise computing and contribute
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Federated learning (FL) is a privacy-preserving distributed learning paradigm that allows different clients to create a shared AI models without having to share their data. Despite these advantages
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in distributed database systems, information retrieval, computer networking or semantic web. The post does not involve working outside of the UK for over 30 days in a row or over 90 days in a year. For
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in distributed database systems, information retrieval, computer networking or semantic web. The post does not involve working outside of the UK for over 30 days in a row or over 90 days in a year. For
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working will be considered. Contract type: Fixed term contract Fixed Term Period: For 24 months Salary: Full time starting salary is normally in the range of £37,337 to £41,478 per annum. Apply by: 19/08
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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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Organisation Cranfield University Faculty or Department Faculty of Engineering and Applied Sciences Based at Cranfield Campus, Cranfield, Bedfordshire Hours of work 37 hours per week, normally
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across Personal Online Datastores (pods) hosted on distributed pod servers, addressing both keyword-based search and SPARQL querying. EPRESSO will build on and extend existing frameworks and systems