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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
/Qualifications Strong proficiency in at least one of these domains: astrophysics, data science (statistics, inference, and machine learning), or physical remote sensing/Earth observation. Strong skills in
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data. Develop and apply machine learning models to estimate uncertainty in climate impact statements. Analyse spatial and temporal patterns and trends in climate-extreme impacts. Cross-validate
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; Distributed multi-agent sensing and cooperative positioning algorithms; Machine learning and data-driven methods for ambient awareness. Working Environment: The PhD will be conducted at the University
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software engineering, computer science, data science, bioengineering, bioinformatics, engineering, physics or related Experience in either machine learning or computational biology. Interest in both
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software engineering, computer science, data science, bioengineering, bioinformatics, engineering, physics or related Experience in either machine learning or computational biology. Interest in both
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to apply Website https://cv.newton-6g.eu/ Requirements Research FieldEngineering » Computer engineeringEducation LevelMaster Degree or equivalent Research FieldEngineering » Electrical engineeringEducation
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democratization of approaches using artificial intelligence based on Machine Learning (statistical AI), data lakes have also been proposed [4,5]. Objectives: Monitoring farming and agronomical activities is based
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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, cell biology, time-lapse microscopy and single cell analysis. You will work in a dynamic and highly interdisciplinary team including computer scientists, experimentalists and clinicians. You will be
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engineering (focusing on deep learning for computer vision), and the division of statistics and machine learning at the department of computer and information science (focusing on the theory behind machine