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of massive galaxies. A series of zoom-in cosmological simulations has been developed by the collaboration in order to understand the physical processes governing the extreme phases of early mass assembly in
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scientific excellence on zeolites and porous materials. • Conduct high-level research in zeolites and porous materials. • Mentor and train early-career researchers in both theoretical and practical skills
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of open science, EIDA will also develop open-source tools for the collection, study, critical edition, and visualization of diagrams through a web-based interface inspired by the DISHAS platform dedicated
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the Quantitative Imaging Platform of Villefranche (PIQv; https://sites.google.com/view/piqv ), which oversees the operation of the tools that the team develops. Those tools include imaging sensors, such as the
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-environmental data cube, including establishing a robust GitLab environment Supervising the development of new data products and user-friendly web applications Serving as the central point of contact for data
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advanced seismic methods (including array processing, machine learning, and potentially distributed acoustic sensing) to develop novel approaches for monitoring unsteady and non-uniform flood flows across
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of early-career scientists, aiming to develop innovative and sustainable materials for health and medical technologies. The selected candidate will contribute to advanced research projects on functionalized
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. Fluid Mech., 2022, 2023; Obligado et al., Chemical Eng. Sci., 2025]. Several fundamental questions remain open: What are the mechanisms that govern the formation and evolution of these mesoscale
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aims to provide a renewed historical and theoretical analysis of definitions and axioms, in particular axiomatic definitions. The research developed at the IHPST (where the recruited person will work) is
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the Zwicky Transient Facility (ZTF) and develop cosmological analyses with the supernova probe. The successful candidate will devote ~30% of their time to the ZTF group's general efforts to help construct SN