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Field
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-frequency characterisation. Investigate and minimise measurement artefacts associated with grounding, shielding, impedance, parasitic effects, noise and signal integrity. Characterise and compare different
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Department. About the project TrainGate uses trackside inspection portals to monitor passing trains at operating speed. Images, acoustic and vibration signals, and identification data are combined to detect
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sciences, biomedical engineering, or psychology; good command of English (minimum B2 level); proficiency in using data analysis software (familiarity with Spike2 software is an additional asset); basic
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image data. The research explores how AI-driven analysis can move beyond manual reverse-engineering workflows by automating feature extraction and structural interpretation while remaining robust to noise
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structural systems and ULS / SLS design concepts Experience in structural dynamics and/or vibration analysis is an added asset Familiarity with finite element modelling (e.g. ABAQUS) and probabilistic methods
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research. You have a good knowledge of and/or a strong interest in biomechanics and human motion analysis. Knowledge of or a strong interest in collecting experimental data (e.g., structural vibrations and
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of mechanical systems are offered for students in computational engineering. Our research addresses questions related to mechanical vibrations, rotor dynamics and sensitivity analysis. Applications are found in
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: ▪ Implementing physical-layer security strategies derived from theoretical work, such as wiretap codes, artificial-noise transmission, secure beamforming, physical-layer authentication, and channel-based secret
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characterised through the analysis of vibration responses generated during train passages. With every train passage, a comprehensive set of dynamic response data will be collected, creating a continuously
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skills (evidenced by high grades) are required Prior research experience in problems related to fluid mechanics, structural vibrations, model reduction or control is expected Experience in nonlinear