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, machine learning (PINN, supervised learning) - Python/PyTorch programming - Autonomy, curiosity, and adaptability - Excellent writing skills Specific Requirements The doctoral student's host laboratory is
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tasks and zero-shot evaluation in linguistic analysis. Profile • Master’s degree (M2) or PhD in computer science, NLP, machine learning, deep learning, or a related field. • Strong experience in machine
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Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP) | Paris La Defense, le de France | France | 28 days ago
a postdoctoral researcher to work full-time on the DiscoReel project. The postdoc will work on developing machine and deep learning methods for epidemic modeling, integrating them with mechanistic
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/chercheur-fh-en-simulation-des-deformations-des-tis… Requirements Research FieldEngineering » Computer engineeringEducation LevelPhD or equivalent Research FieldBiological sciences » Biological
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, involving expertise in optics, electronics, image and data processing, chemistry, and biology. With the support of several European funding programs, the team is building a data science and machine learning
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FieldMathematicsYears of Research Experience1 - 4 Additional Information Eligibility criteria - Thesis in natural language processing with machine learning, - mastery of NLP and machine learning methods and tools
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 17 days ago
. [9]). We are particularly interested in improving the selection of transmission opportunities (e.g., using precomputed sequences), possibly constructed with machine learning techniques (as in [8]). We
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team at the Laboratoire d'Informatique de Grenoble (LIG). GetAlp conducts research in NLP, machine learning, evaluation, and interpretability. The project will be supervised by Maxime Peyrard (CNRS
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difficult to couple with basin simulators. Geochemical metamodels, particularly those based on machine learning, can significantly reduce computation times while maintaining physico-chemical consistency