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reconstruction algorithm (CAVERNS-WatChMaL) to atmospheric data from Super-Kamiokande and T2K. They will carry out the first Super-Kamiokande oscillation analysis based on a deep-learning algorithm, with the
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to tissue engineering and to establish alternative experimental models to animal testing (NAM). The work will be carried out on the INGESYSBIO meta-platform: Engineering of native or reconstructed
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P2S2 project: developing precise parton shower algorithms and studying their consequences in jet physics. - Develop a parton shower algorithm that is precise to the next-to-single log for ee collisions
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OLED devices. Finally, the design and integration of wavefront-shaping functionalities will aim at demonstrating a first prototype of a directional meta-OLED capable of generating structured light. The
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. sediba). - Develop statistical shape models and contribute to the training of hybrid AI-mechanical meta-models (model reduction). - Contribute to the project's deliverables: scientific publications
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and distributed sensing applications over optical fibers. The work will involve advanced manipulation of the phase of ultra-stable lasers, the development and implementation of advanced modulation and
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often lack the resolution and physical detail needed to accurately represent key glacial processes at the watershed scale. This dissertation will develop a coupled, distributed glacio-hydrological
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consist of incorporating our physical findings into the GlaDS model by representing a distributed drainage system in which conduits and cavities are connected in series. The candidate will be required to
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includes approximately 150 people - researchers, teacher-researchers, engineers, technicians and PhD students - distributed across 15 research teams and 4 technical platforms and services. The activity will
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algorithmic approaches and be conducted in the context of wireless networks, the Internet of Things (IoT), distributed learning, or edge computing infrastructures. The research topics may include, the