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– development of scenarios for the network analysis. --- Model development – development of a model that enables the analysis of the impacts of adding sensing capabilities. --- Model implementation
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impacts of Iodine-131 releases, based on detailed knowledge of its physico-chemical processing in the atmosphere including the important inter-halogen reactions. Model findings will be cross-compared
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YOUNG RESEARCHER IN THE FIELD OF EARLY DETECTION OF THE HEALTH STATUS OF PLANTS USING REMOTE SENSING
Mathematics » Statistics Geosciences » Other Technology » Remote sensing Engineering » Agricultural engineering Computer science » Programming Computer science » Informatics Computer science » 3 D modelling
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collaboration between multiple research groups led primarily by Professor Tarek Abdoun and Professor Mostafa Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling
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current and anticipated traffic demands. In this context, it is crucial to design performance models associated with specific network configurations. Analytical models must be complemented by simulation
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Keen to push the frontiers of multiphase reactor modeling and accelerate the scale-up of emerging net-zero technologies? Join us at the Department of Chemistry and Chemical Engineering ! About us
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 4 days ago
LLM, VLM and Foundation Models. Good knowledge of robotics. Languages: English (English is the official language of the team and many members do no speak French). Proactivity and curiosity, daily
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI SCIENZE GIURIDICHE | Italy | 4 days ago
architectures combining LLMs, symbolic reasoning modules, and structured legal knowledge bases, defining evaluation metrics, and providing technical-scientific and project management support. Where to apply
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), Multilayer Perceptron (MLP), Autoencoders, Convolutional Neural Networks (CNNs), and Kolmogorov–Arnold Networks (KANs). Desirable knowledge of Gradient Boosting models such as HistGBM, LightGBM, and XGBoost
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datasets or wildlife imagery Familiarity with data annotation tools and practices for large-scale datasets Knowledge of model deployment and optimization (e.g., ONNX, TensorRT, model quantization) Experience