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oscillation analyses • Practical Experience of deploying state-of-the-art machine learning techniques Desirable: • Ability to develop and apply new concepts • Verbal and written communication skills • Ability
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(segmentation analysis by machine learning) and automatic language processing on large quantities of digitised historical photographs and their metadata. - management, enrichment and structuring of project data
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the Institute of Applied Physics in Florence, Italy (IFAC) and to conferences in Europe to present scientific results. Knowledge of inverse methods, statistics or machine learning Knowledge of remote sensing from
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explainability will be also covered in tight collaboration with medical doctors and radiologists involved in the projects. Key Skills, Experience and Qualifications PhD in machine learning, computer vision or a
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 months ago
capabilities of Machine Learning (ML) models have made Artificial Intelligence (AI) able to tackle challenges ranging from vision and graphics to natural language, and even creative tasks. These improvements
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integration (including environmental sensors and eye-tracking technologies), strong machine learning and deep learning skills (especially embedding models and spatial data analysis), and experience in
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processing, involving machine learning techniques, as well as active participation in data collection from the detectors deployed on site. - Analysis of particle physics data applied to muography: filtering
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13 Feb 2025 Job Information Organisation/Company Ecole Centrale de Nantes Research Field Engineering » Geological engineering Engineering » Computer engineering Engineering » Computer engineering
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and machine learning Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR8254-SYLDES-005/Default.aspx Work Location(s) Number of offers available1Company/InstituteLaboratoire
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the CVRPTW, incorporating energy consumption aspects and autonomous vehicle fleet constraints. Adapt the solver for dynamic problem-solving and integrate machine learning (ML) or reinforcement learning