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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 16 days ago
, curious, autonomous, proactive and dynamic. A specialization in optimization, machine learning, statistical learning or game theory is appreciated. Research experience is a plus. LanguagesFRENCHLevelBasic
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 12 days ago
hyperscanning neuroimaging data, using advanced statistics and machine learning methodologies for temporally-sensitive data, such as GLMM, Random Forests, LSTM, etc.. Use of MatLab for pre-processing, and
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or machine learning, proficiency in deep learning techniques (CNN, VIT, diffusion, GAN) Good understanding of the mathematical foundations of machine learning Mastering python and related AI software
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undergraduates in scientific research projects. ESSENTIAL DUTIES & RESPONSIBILITIES INCLUDE: 1) Computer simulations of protein structure and computational protein design of small peptides and proteins. 2
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statistical and/or machine learning methods, in particular for data integration tasks, would be a plus Previous experience in building and interacting with relational databases (e.g., PostgreSQL) and APIs would
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://www.academictransfer.com/en/jobs/357341/postdoc-position-on-federatedco… Requirements Specific Requirements We are looking for a researcher who sits at the intersection of Pervasive/Mobile Computing and Machine Learning
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machine learning model to rule out heart attacks in the emergency room, which has the potential to translate to large savings for healthcare systems in the world, (2) a computational modelling to assist in
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 17 minutes ago
, seasonal and solar cycle dependent variabilities. These different phenomena make characterization of regional ionospheric dynamics a complex problem. New observational capabilities and sophisticated data
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materials and technologies. Using advanced computational modeling and machine learning, we seek to elucidate the mechanisms governing the self-assembly of lignin in different solvents and the formation
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the development and/or implementation of algorithms and/or computational pipelines Background/experience in building statistical and/or machine learning methods, in particular for data integration tasks