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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | about 1 month ago
personalization algorithms. The project will leverage EvidenceB's extensive deployment infrastructure to work with authentic large-scale educational data and validate innovations in real classroom settings. In
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algorithm-driven sensing systems, remote sensing and multi-modal sensor integration Applicants do not need to cover all areas listed above but should bring strong expertise in at least one and a broad
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implement algorithms for image processing and analysis of multisensor data (RGB, LiDAR, hyperspectral). Design and implement explainable AI (XAI) models for the detection and quantification of grape berry
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record of analysis, interpretation and presentation of –omic related datasets, which can additionally include algorithm, pipeline, or database development. The ideal candidate will have developed a method
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, Effects, and Criticality Analysis (FMECA), functional FMECA, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault
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programming languages like Fortran, Perl, HTML/CSS, and Python is helpful. Experience working with large data sets and complex statistical algorithms is strongly preferred. The applicant should be able to solve
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automation and simulation-driven optimization of high-frequency systems using machine learning * development of optimization algorithms and numerical modeling procedures * development of simulation models
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Geometry, Statistical Learning Theory, Statistical Inference, and Information Geometry. (2) Computing for AI: Programming Language Theory, Algorithm Theory, Combinatorics, Optimization Theory, and
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in medical image analysis. The ideal profile should demonstrate experience in developing deep learning algorithms applied to radiological imaging, particularly in breast and thoracic domains. Knowledge
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seeking to recruit one post-doctoral researcher. Job Description The candidate will participate in the R&D activities of FORTH-IESL within the COLOURS project, working on the development of algorithms and