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qualifications: MSc university degree in physics, mechanical engineering, or mathematics. High motivation for teamwork and good communication skills. Experience in nonlinear dynamics and /or random vibrations and
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Arts et Métiers Institute of Technology (ENSAM) | Paris 15, le de France | France | about 1 month ago
library of models covering various physical phenomena (e.g., damped vibrations, wave propagation, thermal diffusion). This harmonized library will serve as a reference framework for this upcoming project
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friction governs nonlinear vibration and damping in assembled structures. Job description Many high-performance structures, from spacecraft to offshore structures, rely on assembled components
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noise and sensor uncertainties. Applied Artificial Intelligence and Data AnalysisProficiency in multivariate analysis techniques (PCA, regression, clustering) and predictive risk models; Experience with
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structures, vibration and noise control, metamaterials, nonlinear dynamics, rotor dynamics, MEMS/NEMS, structural health monitoring, and biomedical acoustics. Essential Functions Teach graduate and
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cavities, beam scanning, imaging, CW/pulsed laser systems, two-laser Raman thermometry, frequency and time domain thermoreflectance, ultrafast and nonlinear spectroscopy), as well as electro-optical signal
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, energy materials, soft materials, and bio-mechanics. (2) Vibrations and Acoustics ? areas of interest include smart materials and structures, vibration and noise control, metamaterials, nonlinear dynamics
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stimulation on known force–distance laws and binding kinetics. Situations that will be investigated include: Weak electrolytes, where AC electric fields polarize surfaces and induce nonlinear electro-osmotic
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display intricate spatiotemporal dynamics that encode rich informational content. However, analyzing such interactions remains challenging due to the high dimensionality, nonlinearity, and noise inherent in
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combines both short-memory components (correlations that decay rapidly, typical of noise or local oscillations) and long-memory components (power-law persistent correlations over large time scales