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of the mines must also be considered. Recent advances in the geotechnical and geomechanical fields have led to a significant increase in the usage of machine learning (ML), thanks to its computational power and
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machine learning. We particularly value depth of knowledge, originality, and the potential for cross-disciplinary innovation. Relevant application areas may include (but are not limited to) natural
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. The candidate must be able to communicate in English (oral and written). The knowledge of the French language is not required. The candidate must have a strong interest in machine learning. Skills in
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properties changes. - The demonstration of the tear detection with machine learning classification applied directly on S-parameters of the MWI system without solving the inverse problem. The objective
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. The objective of this thesis project is to develop hybrid models that integrate electrochemical principles with machine learning techniques to analyze data from electrolyzers, predict performance, assess lifespan
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parameter estimation using Bayesian inference, and/or the exploitation of Machine Learning (ML) based algorithms to reduce false positives caused by human generated interference signals in the observational
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(formulation, algorithms, applications in structural mechanics), HPC computing, reduced-order modelling, machine learning, Vibrations and structural dynamics, architected materials, Additive manufacturing
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machine learning approaches to integrate single cell and spatial analysis in order to identify molecular signatures and pathways underlying radiation-induced effects. Collaboration: Work in close
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, CNRS, I3S, Sophia-Antipolis, France) Collaboration: Luca Calatroni (Luca.calatroni@unige.it), Machine learning Genoa Center, Italy. Context and Post-doc objectives Conventional optical microscopy
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single micro-sphere of frozen water. This bulkiness presents a significant limitation, and the emission has no directional control. This PhD thesis will build on a decade of research into novel laser