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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 15 days ago
to be analyzed (for example in the IDE via Language Server Protocol). Context Today, static analysis can be integrated into a model-driven engineering (MDE) approach to transform source code into usable
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for interdependent or co-evolving telecom and urban infrastructures driven by real-world data, surpassing state-of-the-art synthetic models; collecting and integrating diverse datasets, including entity matching; and
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provide detailed information on local deformation mechanisms at the microscale, while numerical simulations and data-driven approaches will enable the development of predictive models capable of linking
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Faculty of Engineering and Physical Sciences EPSRC Project Proposals 2026/27 (jobs.ac.uk) Project Link via the 'Apply' button above Project Title: Machine Learning Driven Corrosion Modelling in Bio
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detailed information on local deformation mechanisms at the microscale, while numerical simulations and data-driven approaches will enable the development of predictive models capable of linking
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Computational Mechanics. Solid background in continuum mechanics and numerical modeling Strong interest in machine learning and scientific computing Experience with numerical methods for PDEs and data-driven
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for magnetic particle transport in fluid flows and validating the results through a laboratory-scale reactor. It combines numerical modeling, AI methods, and hands-on experimental work in the context of advanced
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on correlation-based machine learning. When an agricultural system fails due to compounding climate extremes - like a simultaneous heatwave, drought, and ozone pollution spike - standard models can forecast the
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Computational Mechanics. Solid background in continuum mechanics and numerical modeling Strong interest in machine learning and scientific computing Experience with numerical methods for PDEs and data-driven
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, imaging and diagnostic). However, there is currently no generic, metrology-grounded AI/ML framework that fuses these heterogeneous data with physics-based models to create trustworthy, asset-specific