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FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria PhD in computer science, deep learning, or data science. Experience with multimodal models for biological data. Website
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Your Privacy When you visit any website, it may store or retrieve information on your browser, mostly in the form of cookies. This information might be about you, your preferences or your device and is mostly used to make the site work as you expect it to. The information does not usually...
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and economy that respect people and their environment. We are looking for our future postdoctoral researcher in optimization for statistical learning to join the Image, Data, Signal (IDS) department
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responsibility of developing predictive tools based on machine learning for the analysis and interpretation of Raman vibrational spectra applied to battery materials. The successful candidate will design and
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on the development of advanced artificial intelligence and machine learning methods for genome interpretation, with a particular emphasis on modeling the relationship between genetic variation and phenotypic outcomes
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automated configuration mechanisms based on fingerprinting and machine learning to ensure traffic analysis remains faithful to the behavior of the monitored machines. Finally, you will validate your solutions
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, with locations on the Ecully and Lyon-Tech La Doua campuses. It employs around 200 people, including 121 permanent staff. The INL is a major player in the Research and Teaching Cluster. This position is
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(HORIZON-INFRA-2024-TECH-01-01 – R&D for the next generation of scientific instrumentation, tools, methods, and solutions for RI upgrade), this position focuses on data curation activities under Work Package
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scientific ecosystem in semiconductors, gathering CEA, CNRS, Université Grenoble Alpes, major European facilities (ESRF, ILL), and high-tech companies such as Lynred, Aledia, Soitec, and STMicroelectronics
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze