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Field
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-MID prototyping and performance optimization of structure-embedded sensors and nanogenerators. Depending on applicant’s skillset the research objectives may include implementation of AI-assisted in
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nanoparticles that generate heat due to energy losses upon periodic alignment along an applied alternating magnetic field. Although numerous nano-objects have been manufactured up to now, the spatial diffusion
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the bearing. To optimally re-lubricate, it is vital to understand this mixing process. Currently, the scientific knowledge of re-lubrication is non-existent. This project will build new knowledge on several key
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, numerical process simulation, and advanced characterization techniques (synchrotron, TEM, EBSD), will be implemented. The ideal candidate will hold a Master's degree or an engineering degree in Materials
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centre also benefits from numerous state-of-the-art technological platforms, offering access to high-calibre equipment and recognised technical expertise. The PhD thesis will be supervised by Raphaël
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mantle in order to determine if this composition is the same as that of the nebula or the solar wind material. In the project we investigate the degassing processes of magmas experimentally and numerically
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while maintaining computational efficiency through lower-fidelity simulation of non-critical regions, (ii) virtual sensing techniques for load and stress estimation from limited and optimally placed
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with a background in fluid mechanics or thermal engineering. Given the scope of the research project, a strong interest in both experimental work and numerical modeling is essential. Familiarity with
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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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, biophysics, biochemistry, and molecular modeling, developing experimental and numerical approaches for the study of complex molecular systems. Within this institute, the Biophysics of Complex Systems team