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Field
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NPL, the UK’s national metrology institute, is developing a fully functioning, thoroughly characterised, local area quantum network (QLAN) linking heterogeneous nodes across its site. It will make
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, spanning domains from automotive and avionics to healthcare, increasingly rely on distributed and multi-layered control architectures. These systems comprise interconnected computing nodes, actuators and
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-informed data analytics tools for the predictive maintenance (PdM) strategy applications to high-value critical assets. Among others, the recently developed Physics-informed Neural Network (PINN) technique
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-2026 JANUARY 2026 start ONLY For April and October starts please use the relevant application. This form is only to be used by those self-funded applicants seeking a place on a research degree programme
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-2026 April 2026 start ONLY For January and October starts please use the relevant application. This form is only to be used by those self-funded applicants seeking a place on a research degree programme
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are part of the programme. The research is funded by the Centre of Propulsion and Thermal Engineering at Cranfield University. The work will be conducted at the Cranfield icing wind tunnel (IWT) based
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each year. Modern applications—from power grids to vehicle platoons—depend on large networks of autonomous subsystems. Without a solid theoretical underpinning, ensuring both collective objectives
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collaborative studentship between the University of Edinburgh and the National Quantum Computing Centre (https://www.nqcc.ac.uk ). The position will be registered and hosted at the University of Edinburgh and
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networking activities organized by the school. There are opportunities to interact with several UK and EU collaborators and travel to these labs for personal development opportunities. Supervisors:Professor
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emissions from transport. Decarbonising aviation is a vital part of achieving net zero. Hybrid and ‘all electric’ aircraft technologies offer a pathway to net zero. The electrification of aircraft, for both