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Deep Learning-type methods. The focus will be on geodesic methods, the search for paths of minimum length according to an adapted metric, imposing for example a penalization of the curvature. In addition
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will focus on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural
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of Research Experience1 - 4 Additional Information Eligibility criteria - PhD in Phonetics/Phonology, Computational Linguistics, Automatic Speech Processing/Machine Learning or relevant related fields
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(Robert Whitney). The Grenoble part of the team currently comprises R. Whitney, 2 PhD students and 2 postdocs, in addition to PhD students and postdocs in the Singapore part of the team. Each team member
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This position will consist of using "deep learning" methods, in particular CNNs and "transformers" for the processing of data from the IASI instrument from CNES. These observations are brightness temperature
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FieldComputer scienceYears of Research ExperienceNone Research FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria PhD in computer science, deep learning, or data science
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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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on the Pierre et Marie Curie campus in central Paris. It comprises ~90-100 researchers, professors, PhD students and post-doctoral fellows, and conducts research in the fields of energy (electrochemical storage
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» Computational chemistryYears of Research Experience1 - 4 Additional Information Eligibility criteria - PhD in theoretical chemistry applied to materials, materials physics, computer science/applied mathematics
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, having a wide range of applications, from astronomical imaging to computational photography. In recent years, (deep) learning-based solutions have obtained state-of-the-art performance in many applications