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, this PhD thesis will focus on the characterization of multipolar electrograms (EGM) through graph signal processing (GSP). The underlying hypothesis is that local propagation patterns in AF are associated
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parameters from parasite genetic data; cf., viral genomic epidemiology, where bifurcating trees capture the ancestry of DNA sequences, and human population genetics, where the ancestral recombination graph
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for magnitudes between 7 and 8. Research program The project will aim to adapt PEGSGraph (Juhel et al., 2024), a graph neural network we designed for rapid magnitude estimation from PEGS (Hourcade et al., 2025) in
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with GREYC (UMR CNRS 6072), the computer science laboratory of Université de Caen Normandie, particularly in machine learning and graph-based approaches. Depending on the scientific questions addressed
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frameworks with the competencies actually required in professional environments. The project leverages competency frameworks, ontologies, knowledge graphs, occupational taxonomies, and job advertisement
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and motivated PhD student to contribute to the development of the next generation of DNA computers, capable of processing large molecular databases. The project will combine concepts from molecular
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
Framework Programme? Not funded by a EU programme Reference Number 2026-10332 Is the Job related to staff position within a Research Infrastructure? No Offer Description Work Environment The PhD candidate
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Positions PhD Positions Application Deadline 28 Jul 2026 - 20:00 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Oct 2026 Is the job funded through the EU
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essential for learning complex distributions over structured data such as text, graphs, and biological sequences. Developing and understanding models for dis- crete spaces is therefore a key challenge in
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 1 month ago
retrieval: reconstructing the original digital data from the sequenced symbols. This PhD project focuses on the first and fourth challenges, by developing joint compression and error-correction algorithms