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the Acoustics Research Centre (ARC). Its facilities are complemented by extensive experimental hardware, including the wide range of vibro-acoustic sensors and multi-channel acquisition systems required by
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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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position is part of the AI2 (Algorithmic Assurance and Insurance) research initiative, an ambitious programme supported by the UK Prosperity Research Scheme with partners from both industry and academia. Our
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decentralised algorithms, meta-information data structures and indexing techniques to enable large-scale data search across Personal Online Datastores (pods) hosted on distributed pod servers, addressing both
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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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(SDR) platforms and characterise them in the presence of interference in a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide enhanced interference resilience
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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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beginning in this role. We will require all candidates invited to interview to apply for NSTIx clearance. In this role you will: Design and test detection and estimation algorithms utilising artificial
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signal processing Extensive research experience and scholarship on radar systems and signal processing, ideally for distributed radar sensors, and general knowledge of the effects of oscillator
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an emphasis on the digital transformation of the composites industry. The post aims to lead and support research linked to: Multiphysics simulations for composites. Sensor integration for real-time monitoring