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disciplines and involve expertise in optics, electronics, image and data processing using machine learning, photophysics, chemistry and biology. The position is therefore particularly well suited for candidates
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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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). • Advanced quantitative analyses (machine learning, computer vision, multilevel statistics). • Creation and use of Python code for advanced analyses. • Management and monitoring of complex transgenic lines
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ExperienceNone Additional Information Eligibility criteria - Holding a doctoral degree in particle physics - Experience in C++ and Python programming is desired - Experience in training and using Machine Learning
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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 | Villeneuve la Garenne, le de France | France | 2 months ago
, CIRAD AMAP, CIRAD PHIM, CIRAD PBVMT, INRAE ePhytia, INRAE IGEPP, INRAE LISAH, IRD EGCE, IRD IEES, Univ. Paris Saclay, TelaBotanica). This is a postdoctoral position in Machine Learning, more
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of autonomous mobile machines integrating perception, reasoning, learning, action and reaction capabilities. The team's main research areas are: architectures for autonomous robots, human-robot interaction
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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
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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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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