47 power-"https:" "https:" "https:" "https:" "https:" "https:" PhD positions in France
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 1 day ago
1389-1286, https://doi.org/10.1016/j.comnet.2026.112148 . [2] I. Alla, S. Yahia, V. Loscri and H. Eldeeb, "Robust Device Authentication in Multi-Node Networks: ML-Assisted Hybrid PLA Exploiting Hardware
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ability to transport RNA, with the physicochemical properties of liposomes designed to promote membrane fusion and enable magnetic guidance. The resulting nanoplatform should therefore enable the targeted
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is essential. Indeed, the intermittent and variable nature of renewable energy sources such as wind and solar power makes storage necessary. Redox-flow batteries, which allow for the decoupling
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within the Solid-state Quantum Technologies team (S2QT – https://solidstatequantumtech-l2c.fr/ ) of the Charles Coulomb Laboratory in Montpellier. The doctoral work will be supervised by Vincent Jacques
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their metabolic properties, their ability to form and maintain tumours, and their response to treatment. The PhD student will also investigate the involvement of these proteins in interactions between tumour cells
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of synchronisation and complex dynamical systems; • Ability to work independently while contributing effectively to an interdisciplinary team. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR5263
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The i3S laboratory (https
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qualities_: Independence, organisational skills, attention to detail, the ability to work as part of a team, and good communication and writing skills Where to apply Website https://emploi.cnrs.fr/Offres
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STLO) (https://eng-stlo.rennes.hub.inrae.fr/ ). This work is part of the “Predicting the browning of dairy powders by kinetic modeling of Maillard reaction and caramelization during drying and storage
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from massive datasets. Their ability to capture transferable knowledge offers a unique opportunity to rethink the modeling of physical interactions. The central idea of this PhD is that a model trained