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predict interaction effects. Unlike robot-specific neural network models, the proposed approach aims to learn a universal representation of local interactions (fluid-structure, robot-robot, robot-object
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-fidelity modeling approaches combining simulations of different fidelity levels, ranging from RANS calculations to high-fidelity LES, possibly associated with various levels of geometric or physical
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climate models. Paleoclimate reconstructions allow us to describe natural hydroclimatic changes in the Amazon under different forcings. Existing records reveal past variations in Amazonian hydroclimate
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tomography, high-pressure reactor) with numerical modelling (COMSOL) to quantify and predict dissolution. • Select and characterise biogenic shells (foraminifera, pteropods) from oceanographic cruises
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topology changes and transitions between different operating modes also constitutes a major challenge. Furthermore, this thesis will focus on the frugality of the proposed approaches, seeking to reduce the
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, if possible with a focus on modelling/numerical simulations. • A good level of Python programming is required. • A level of scientific English sufficient to conduct research and build international
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the unique features of myosin 18 enable it to fulfill its regulatory role, using modeling and simulation approaches. Various computational methods will be employed to investigate the structural and dynamic
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combine laboratory experiments, numerical simulations, artificial intelligence and field observations to address outstanding questions in physical oceanography, atmospheric sciences, physical limnology
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analysis, based on particle-in-cell (PIC) simulations, in order to (1) compare the effect of different types of broadband sources on the growth and saturation of three-wave coupling instabilities (Raman and