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Field
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algorithms to support semantic search and generate summaries of tax rulings. Collaborating in developing a semantic repository for tax rulings and court decisions. Preparing scientific publications based
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algorithms to support semantic search and generate summaries of tax rulings. Collaborating in developing a semantic repository for tax rulings and court decisions. Preparing scientific publications based
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algorithms to support semantic search and generate summaries of tax rulings. Collaborating in developing a semantic repository for tax rulings and court decisions. Preparing scientific publications based
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Infrastructure? No Offer Description The AITAX project aims to address the complexity and dynamics of modern tax regulations by developing a cutting-edge AI solution for automating the analysis and processing
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on signals and complex systems. Gipsa-lab develops projects in the strategic fields of energy, the environment, communication, intelligent systems, life and health technologies, and language engineering
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the development of algorithms tailored to specific problems, even if based on higher-level search strategies. In combinatorial optimisation, this is justified primarily by the fact that the decision space and the
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 1 month ago
preserved at ambient temperature provided it is protected from light and humidity. Goal The goal of the project is to develop an algorithm to allow robust retrieval of data in the context of DNA-based data
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of the ICCVS is the development of personalized vaccine against non-small cell lung cancer (NSCLC). The approach is based on the use of cancer specific T cells that are selected by the special algorithm
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and build a light-sheet encoded-illumination microscope Characterize the system Sample Chamber Development Development of Decoding Algorithms Single-Plane SR Imaging Volumetric Imaging of selected
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-heuristics, has long favoured the development of algorithms tailored to specific problems, even if based on higher-level search strategies. In combinatorial optimisation, this is justified primarily by