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improves the performance of ROMs, making them more applicable to real-time structural health monitoring, vibration analysis, and control design. This research offers real-world impact across several
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14th September 2025 Languages English English English The Department of Electronic Systems has a vacancy for a PhD Candidate in Wind Turbine Noise Prediction in the Norwegian Context Apply
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the recording of substrate-borne vibrations produced by earthworms (and other invertebrates) in situ. To fully exploit this emerging technology there is a need to unravel the meaning within the data. As such
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significantly reduce the amount of vibration data to be stored on edge devices or sent to the clouds. Hence, this project's results will have a high impact on reducing the hardware installation and operation
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Environmental Protection Agency (EPA) Project “Noise 2050” 3 × Fully-Funded PhD Scholarships (4 years, expected start: autumn 2025 — flexible) The EPA-funded Noise 2050 project will forecast
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the recording of substrate-borne vibrations produced by earthworms (and other invertebrates) in situ. To fully exploit this emerging technology there is a need to unravel the meaning within the data. As such
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to integrate floating offshore wind turbines and wave energy converters to capture wind and wave energy. The hybrid system’s dynamic responses will be investigated and advanced vibration control technologies
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noise models, leading to metrics devoid of assumptions about noise impacts (e.g., cross-talk or non-Markovian noise in gate fidelities). As shown by the supervisory team, non-Markovian noise can be a
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noise models, leading to metrics devoid of assumptions about noise impacts (e.g., cross-talk or non-Markovian noise in gate fidelities). As shown by the supervisory team, non-Markovian noise can be a
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algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical optimization of QML algorithms Noise mitigation in relation