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imaging. It will: • establish a robust methodology for fine-grained comparison of complex embryonic morphologies, • design neural networks adapted to the specific challenges of 3D+time microscopy, • provide
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this process is not understood. Is VDAC needed for insertion of Bcl2 proteins in the membrane, for their activation, or for both? Biochemical and structural data are necessary to decipher the interaction network
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optimization of complex systems, intelligent data and information systems, as well as networks, distributed systems, and security. LIMOS stands out for its interdisciplinary approach, combining theoretical
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learning in neural networks within the ANR-funded MAPLE project, under the supervision of Dr. Bruno Loureiro . Funding is available for two years. Responsibilities Conduct research on the mathematical
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 9 days ago
of the direct ECT problem. The direct ECT problem essentially consists in solving the 3D Maxwell equations, in the harmonic regime, within an heterogeneous medium. The medium, whose geometry may be complex, is
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for separate neural networks, reducing computational complexity and improving the overall efficiency of autonomous navigation.
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Research FieldPhysics » Applied physicsEducation LevelMaster Degree or equivalent Skills/Qualifications Cryoporometry, NMR relaxation, pore network structure LanguagesENGLISHLevelGood
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. Goals of the PhD project include the exploration of the fundamental mechanisms of self-assembly of molecules into nanostructures and networks, forming complex soft materials, such as gels. In particular
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dozen input variables). The foreseen approach would be to build on recent developments in using CNNs for Species Distribution Models (e.g. Deneu et al 2021, Morand et al 2024) to summarise the complex
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 19 days ago
, 3], significant challenges related to running complex AI algorithms such as Deep Neural Network (DNN) inference on lightweight platforms with limited computational power and relying on potentially