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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 17 days ago
modules leveraging deep learning for classical problems such as segmentation and 3D object tracking interfacing machine learning code and the robot using ROS2 contributing to the creation of datasets
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Learning, or a related field. A Master’s degree is preferred. ASR/TTS Expertise Experience in training and fine-tuning Automatic Speech Recognition (ASR) or Text-to-Speech (TTS) models, preferably in
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machine learning (ML) models and optimization algorithms specifically designed for highly dynamic satellite communication (SatCom) systems that can handle networks of varying sizes and configurations
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courses). - Proficiency with computer tools: R, Python, Bash, Perl, Java, SQL. - English: High-level language proficiency. - Willingness, ability to learn, and teamwork skills will be valued. - Experience
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | about 1 hour ago
programming, machine learning (scikit-learn, PyTorch/TensorFlow), ontologies (OWL/RDF), and/or computational cognitive modelling Interest in interdisciplinary research at the interface of computer science
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computational modeling to identify bacterial strains and metabolites that promote or hinder probiotic establishment. By combining multi-omics data with systems biology and machine learning approaches
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adaptation, synthetic data generation, and cross-modal learning to enable models that generalize across defect types and machine configurations. This ensures scalable, accurate defect detection even in low
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machine learning models to estimate individual numbers and distinguish species in complex field conditions. The resulting methods could later be applied to monitor waterfowl and scavengers in Lough Neagh
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should hold a Master's degree in Computer Science, Artificial Intelligence, Computational Linguistics, Data Science, or a closely related field Solid background in machine learning and natural
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-based modeling of hydrological and Earth system processes. The CHAS group conducts world-class research in hydrological and Earth system modeling, large-scale data analytics and machine learning (ML), and