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-angers.fr/poste/l3n5xsoefq-post-doctorante-en-machine-… Requirements Research FieldMathematicsEducation LevelPhD or equivalent Skills/Qualifications Knowledge: • The candidate must have a basic understanding
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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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thesis), with significant skills in the second (typically through their initial training, an internship, or a prior post-doc). We are therefore seeking applications from the remote sensing and geosciences
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models Foundation models represent a breakthrough in AI, as did the shift from traditional machine learning to deep learning. Numerous models become available in the field of Earth Observation and can be
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and extend an existing RL framework currently under submission, which serves as the foundation for this research. The post-doc will enhance this framework by developing advanced methodologies, primarily
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these autonomy and self-adaptation capabilities. Three major challenges have been identified: (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed
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technologies generate unprecedented volumes of molecular data at cellular resolution, opening new avenues for the application of machine learning to fundamental biological problems. The postdoctoral researchers
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of nanodevices and their multiple functionalities for bio-inspired computing. The team includes two permanent CNRS researchers, two Thales researchers, 4 post-docs, and 4 PhD students. Where to apply Website https
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to the LabNBook and UNESS platforms (more than 60,000 cumulative users). Close collaboration with AI engineers, doctoral students, post-docs, and academic partners is planned. The candidate will work on the
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collaboration between the Exa-SofT and the Exa-DI projects and better support multi-linear algebra and tensor contractions in exascale CSE applications and Machine Learning. As part of the collaborative process