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key elements to answer the question of the causes of changes in ozone trends throughout the troposphere. This will involve exploring regional and vertical differences to better understand the dominant
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regimes; and machine learning, capturing complex nonlinear behaviour at the cost of model opacity. BENEFIT synthesises these paradigms by integrating stability analysis directly into machine learning
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systems (LIED, Université Paris Cité), experts in classical atomistic simulations (molecular dynamics and coarse-graining, LMCE, CEA/DAM/DIF), as well as specialists in continuum simulations (finite element
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possibilities for automating the analysis of comic book pages, linking elements together, and generating narration scripts. The EnACA Project aims to develop a toolchain ranging from the automatic analysis
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spintronics team in charge of developing terahertz emitters and field-effect transistors based on two-dimensional (2D) materials such as transition metal dichalcogenides. He will work within the Spintec
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shaping will be central to the study. The numerical model will be based on the boundary element method (BEM) and semi-analytical approaches developed at I2M. The experimental proof-of-concept will leverage
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streaming, and perform a complete landform analysis and glaciodynamical reconstruction of a possible former Kasei ice stream. In detail, the project objectives are: (1) Test the hypothesis that an ice stream
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finite-difference resolvent solver incorporating stabilising filters as well as a domain-decomposition strategy suitable for complex geometries, - Use efficient time-integration methods to compute
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expertise in HCI and education, including adaptive gamification, engagement, learning analysis, and the design of motivational affordances in education. As part of the project, the PhD student will work with
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and with the 2AT team at Institut Pprime to develop a shape-optimisation tool based on resolvent analysis, applied to landing-gear aeroacoustics The researcher will develop a numerical methodology based