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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 7 days ago
, are to be addressed. Objectives: The research of this PhD will be articulated around the concept of useful landmark for localization in complex environments. Indeed, unlike cases where object detection
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, data-driven surrogates) are widely used to obtain fast, approximate predictions. A major scientific challenge is therefore to combine information from models of different fidelity levels in a principled
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to uncertainties and gaps. To relax these constraints and make PINNs more robust, several approaches can be considered depending on the context, each offering different ways to handle uncertainties in physical
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will use and develop Python scripts for analysing results and may participate in the development of codes such as the observation simulator and the improvement of the controller. The proposed thesis will
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developments by the project team regarding advanced crystal plasticity models, different modeling strategies will be explored, including strain gradient plasticity [1,8,9], micromorphic approaches [2], and
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plasticity platform. Different machine learning strategies will be explored to capture the complex relationships between microstructural features and mechanical responses. In particular, the project will
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developments by the project team regarding advanced crystal plasticity models, different modeling strategies will be explored, including strain gradient plasticity [1,8,9], micromorphic approaches [2], and
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 24 days ago
of the Cluster IA ENACT project (https://cluster-ia-enact.ai/ ) that is funding this PhD thesis. In the chair, she wants to push the research in Natural Language to assist humans in different scenarios
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 26 days ago
split over many computing nodes. An important consideration in our context is that, unlike classical data stream, the data is not i.i.d. on the nodes, but stems from the domain partitioning imposed by
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plasticity platform. Different machine learning strategies will be explored to capture the complex relationships between microstructural features and mechanical responses. In particular, the project will