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the development of high-fidelity finite element models to investigate surface wave propagation in soft biological tissues, forming the foundation for subsequent statistical and machine learning
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engineering simulation tools, such as optical ray-tracing software, finite-element analysis (FEA), CFD solvers, or thermal/structural analysis tools. Strong ability to work with integrated optical–mechanical
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of experimental data - Molecular Dynamics and Finite Element calculations. . Metallic nanoparticles (NPs) exhibit unique physico-chemical properties departing from those of bulk materials, primarily due
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of high-fidelity finite element models to investigate surface wave propagation in soft biological tissues, forming the foundation for subsequent statistical and machine learning frameworks that integrate
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micro-electro-mechanical device (MEMS) dedicated to the manipulation and measurement of micro-samples, the coupled gripper-sample modelling using numerical analysis and finite element methods, and the
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advanced modelling approaches—such as finite element analysis —to capture the nonlinear, multi-physics nature of soft materials. By integrating experimental data and validating simulations, your work will
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Engineering, or Aeronautical Engineering. - Knowledge of static and dynamic structural analysis using finite element software. - Knowledge of programming languages applied in engineering. - Experience in
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planned that this PhD expand this for additional loading types and additional response mechanisms. A key factor is use of experimental data with the computing framework enabling a hybrid approach not
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Mechanical Engineering Technology Program with Engineering Design (Fusion 360), CAD/CAE (Solid Works), Engineering Computing (Matlab), Finite Element Analysis (Solid Works) skills preferred. A strong
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Predictive simulation will be developed using finite element analysis (FEA) between LMGC, ICube and LEM3. Experience in poro-mechanical simulation is therefore an asset (Le Floc'h, et al., 2024). In addition