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of diagnostic and prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict the remaining useful life of electronic components, supporting studies in electronic
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sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
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-critical systems. The research will focus on developing AI-powered verification tools, health monitoring algorithms, and compliance assurance techniques that ensure system reliability throughout
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persists, even for the most powerful sensors operating in this way. A drastic departure from this sensing architecture is “multistatic” radar – enacted by a coherent network of spatially distributed sensors
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novel multi-objective optimisation algorithms, to evaluate metrics such as material circularity, system efficiency, cost, and carbon footprint. The University of Surrey is ranked 12th in the UK in
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and misalignment, facilitating the development and validation of diagnostic and prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict the remaining
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address: Dr Fahad Panolan: f.panolan@leeds.ac.uk Project summary The Algorithms group at the University of Leeds (UK) is offering a fully funded 3.5-year PhD studentship on Parameterized Complexity and
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: The occurrence and distribution of species within and around solar parks, identifying key “winners and losers” in terms of biodiversity. How species interactions, including plant-pollinator networks
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public sources, data on the current status of ecological communities in several woodland patches across Wales, encompassing all taxa. The data will comprise species presence and distributions as
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of peatlands under future climate change, incorporating projected outcomes from restoration activities and the identification of environmental tipping points from mechanistic modelling of species distributions