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Field
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-quality acoustic datasets over time; 3. AI methods for removing noise and outliers from the data; 4. AI methods for extracting key features from multi-modal data; 5. AI assisted monitoring of damages in
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responsibilities (dependent on experience level of applicant) Develop and improve multi-temporal InSAR processing algorithms (e.g., time series analysis, phase unwrapping, noise mitigation, filtering, atmospheric
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gain media with low-loss photonic integrated circuits (PICs) has recently enabled integrated lasers with faster tuning and lower phase noise than the best legacy systems, including fiber lasers. In
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theory and modelling. Experience with acoustic/vibrational waves, periodic structures and/or Metamaterials. Experience with experimental measurement techniques for fluid mechanics. TU Delft Delft
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uncertainty, modality dropout, and noise propagation, which can degrade robustness and erode trust in model outcomes. This project aims to create a unified framework for building lightweight, data-efficient
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parts of CBM. Therefore, diagnostics and prognostics of rotating machinery can help to reduce machine downtime and cost. Many techniques such as vibration analysis, current signature analysis, acoustic
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for practical problems” and under this vision, it has contributed many fundamental new ideas in circuit design. The IC Design group has made high-impact inventions in analog filters, thermal noise cancelling