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foundations and principles of Machine Learning, Linear Algebra (vectorial and matricial operations, optimization), with a particular focus on Neural Networks (pytorch), 3) problem solving skills, 4) familiarity
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postdoctoral fellowship at ENS Lyon in the field of machine learning. The position is part of the research project "Neural networks for homomorphic encryption", funded by Inria. Fully homomorphic encryption (FHE
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networks (GNNs) to accelerate therapeutic target identification. GenePPS aims to overcome current limitations of perturbation modelling by integrating large-scale single-cell foundation models with
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(Python required; R, C++ appreciated). Strong interest in network modeling, multi-criteria optimization, or graph theory. Skills in statistics and data analysis. Experience in 3D modeling, phenotyping
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 19 days ago
nationalities. The research project will lay the theoretical foundations for general network steering by: (i) Identifying its genuine concepts and manifestations, (ii) developing tools for its characterization
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of the project is to design, model and simulate neural networks based on magnetic skyrmion nucleation and propagation. The second objective is to fabricate these hardware neural networks, characterize
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techniques; Structural and functional characterization of interfaces and junctions, in particular through nanoscale analyses; Development, adaptation, and optimization of experimental methodologies
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opportunities for independence, international networking, and leadership development in preparation for future fellowships. Where to apply E-mail rita.manco@inserm.fr Requirements Research FieldBiological
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Financial support: 2100-2400 euros/month, net salary The host laboratory is the UMR 6064 CNRS (CARMeN) based in Rouen (Normandy). The research developed within Institute of analytical chemistry and molecular
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is an interdisciplinary effort at the frontier between Biology (Genetics, Genomics), Bioinformatics, Artificial Intelligence (Neural Networks) and Statistics (LMMs). The aim is to join the