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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 4 hours ago
applied mathematics, control, or related fields, with knowledge in several of the following areas: Graph theory and network modeling Dynamical systems and physical modeling (ODE/PDE, multi-agent systems
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, particularly for multi-variable simulations. Knowledge of complex systems modeling applied to urban dynamics. Publications in scientific journals. Personal and Organizational Qualifications: Ability to develop
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different model sizes and deployment settings. Apply and advance model compression techniques, including quantization, pruning, knowledge distillation, low-rank adaptation, and related methods. Conduct
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/123 Research Project: SMART-CM, Simulation and Advanced Modelling of Thromboembolic Risk The successful candidate will work within the framework of the SMART-CM project, as part of a research training
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) and a global ocean model (NEMO). The selected candidate will contribute to the ANR-AIAI project (https://anr-aiai.github.io ). Scientific Context The melting of Antarctic ice shelves by the ocean is a
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in practice conditions, will be modelled as event-like inputs that perturb the system and whose effects unfold over time. Time-independent predictors, including cognitive abilities, personality traits
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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10 Apr 2026 Job Information Organisation/Company CNRS Department INSERM U960 - LABORATOIRE DE NEUROSCIENCES COGNITIVES Research Field Neurosciences Psychological sciences » Cognitive science
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quantify model uncertainties For further information visit our website http://www.fz-juelich.de/ibg/ibg-3/EN/Home/home_node.html or contact us via the contact form. Your Profile: Master’s degree in
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. Proficiency in Python for data analysis and model development (NumPy, pandas, scikit-learn). Working knowledge of SQL and relational databases. Familiarity with at least one ML or deep learning framework (e.g