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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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, decision-making and control using data, have been proposed. For control or management applications, reinforcement learning (RL/DRL), a branch of machine learning, is a promising solution that involves
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solid experience in programming, particularly in Python and JavaScript. Significant experience in data science and machine learning will be highly valued. You like to work in a team while demonstrating
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(including computer science, machine learning or deep learning). Activities Description of the research activities : The post-doctoral researcher will develop the research actions defined in his/her research
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of massive galaxies from the primordial Universe to z~2. This project combines a unique JWST dataset with state-of-the art hydrodynamical simulations and machine learning techniques to understand the origins
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project combines techniques from machine learning, natural language processing (NLP), and knowledge representation to support legal scholarship and decision-making. The position entails close academic
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of Python programming and a deep learning framework, preferably PyTorch. Solid knowledge of image processing, inverse problems, and machine learning. Significant research experience, demonstrated by quality
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Université de Bordeaux / University of Bordeaux | Villenave d Ornon, Aquitaine | France | about 1 month ago
genomic diversity and genetic load from available genomic data for various woody species. For this, you will use the available pipelines from phase 1 of the project and apply machine learning-based methods
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 1 month ago
Cancer Research Center. The team has access to several computing facilities (e.g. IGRIDA cluster) and established collaborations with other Inria/Irisa research teams in the field of machine learning. Our
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statistics and/or machine learning Specific knowledge • Proficiency in scientific computing • Knowledge of machine learning packages in Python or R • Proficiency in English (minimum level B2), as the postdoc