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(scRNA-seq) data, and structural data from cnidarians, and we will develop new algorithms to analyze the evolutionary history of muscle components. You will study the evolution of muscle components during
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for the detection of exoplanets in coronagraphic images. Unlike traditional methods that rely on angular or spectral diversity to differentiate planetary and stellar light, this project is to develop Coherent
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study will leverage existing numerical resources and mobilize advanced methods from software engineering to develop a robust and adaptable framework for manipulating and coupling different models
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10 Apr 2026 Job Information Organisation/Company CNRS Department Laboratoire d'Informatique, Signaux et Systèmes de Sophia Antipolis Research Field Computer science Mathematics » Algorithms
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biopsy can help predict glioma at different stages of this brain cancer, as well as the evolution of the tumor. This part of the project involves designing, developping, and running machine learning
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energy recovery linac (ERL) demonstrator at IJCLab, Orsay. ERLs offer a promising way toward the development of future colliders, particularly by providing excellent beam quality while drastically reducing
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conducted to assess the feasibility of prototypes in terms of activity tracking, updating game elements, and visualisation capabilities. The second objective of the thesis is to develop models and algorithms
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to develop a data-efficient and uncertainty-aware framework for pigment mapping in Cultural Heritage. Heterogeneous spectral and imaging data from different sensors will be jointly exploited, including X-ray
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algorithms have been developed, most based on a hybrid architecture combining transform coding and predictive coding. Standards such as H.264/AVC, HEVC, and VVC follow this principle. While they offer highly
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atmospheric sciences • Knowledge of cloud or aerosol physics • Experience in algorithm development and satellite remote sensing • Good written and spoken English • Ability to work independently as well as in a