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, Infected macrophage populations. Perform parameter estimation using optimization and machine learning approaches Develop numerical schemes for high-dimensional structured PDEs (pseudospectral methods
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 20 days ago
in particular computer vision. Particular topics of interest include visual comprehension, hyperspectral imaging, numerical and parallel optimization, and unsupervised learning. A particular emphasis
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large-scale numerical simulations will generate rich datasets describing the relationship between microstructure, deformation mechanisms, and mechanical response. While physics-based simulations involving
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large-scale numerical simulations will generate rich datasets describing the relationship between microstructure, deformation mechanisms, and mechanical response. While physics-based simulations involving
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about shape optimization and the new opportunities offered by numerical design in turbomachinery. Prior experience in CFD and/or CFD code development (Python, C++, Fortran) would be a significant
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mangament in numerical models, including advanced calibration strategies from data (observations, measurements, other model predictions) and uncertainty reduction. Scientific context Many engineering and
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promising technology for producing large and complex metal component. Although its potential has been widely demonstrated, significant challenges remain in optimizing the process to ensure the quality
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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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. Propose, develop, and test enhancements (e.g., shock-capturing strategies or improved numerical schemes). 3. Idealized supersonic flow simulations: Using the optimized code, conduct idealized simulations
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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