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an external client. Project aims and objectives The project aim is to develop a proof-of-concept portable analytical method for the detection of targeted PFAS molecules, and to demonstrate the applicability
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mechanics, such as inferring the instantaneous state of a fluid’s velocity field from sensors embedded in its boundary. The research objective is to find the best way to embed simple partial differential
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resilient to future change. This project will evaluate potential future land use configurations in several countries, exploring where and how biomass production can support multiple objectives for a
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objective is to find the best way to embed simple partial differential equations into AI-based models to solve fluid sensing problems in a robust and efficient manner. Your role may include developing new
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
engineers detect faults earlier, track system degradation, and make better-informed maintenance decisions. But how can we turn this complex information into something reliable, explainable, and actionable
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of the challenges is fault detection and diagnosis of bearings subject to low (rotational) speed. As vibration/acoustic signals generated by the faults of low-speed bearings are very weak and often covered by strong
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hardware design, and build in fault detection and correction to ensure secure, efficient operation in space systems. The outcome will be a high-performance, fault-tolerant Falcon implementation, enhancing
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Vehicles (UAVs, or “drones”) to scout ahead of a vessel, thus increasing its detection range and allowing more time to effectively react Ultra-fine image spatial resolution: Allowing smaller objects to be
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optimization of batteries against the swelling phenomenon. This project aims at developing scientific machine learning approaches based on the Bayesian paradigm and electrochemical-thermomechanical models in
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therapies to reduce RILF and improve treatment outcomes. Objective 1: Develop multimodal imaging with bioluminescence and contrast-enhanced CT to visualise liver and brain tumours for precise SARRP-guided