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of the mean flow). This study aims at contributing to a better control of the risks related to airborne contaminations in indoor environments by improving the modeling of the resuspension phenomenon. Expected
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9 Feb 2026 Job Information Organisation/Company IMT Atlantique Department Computer Sciences Research Field Computer science Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Application Deadline 15 Mar 2026 - 23:59 (Europe/Paris) Country France Type of...
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research units: GEPEA, IRISA, LATIM, LABSTICC, LS2N and SUBATECH. The proposed thesis is part of the research activities of the team MOTEL (Models and Tools for Enhanced Learning) of the Lab-STICC laboratory
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, data characteristics, and application requirements. The work will focus on proposing models for multimodal data streams, adaptive transmission strategies, and their integration into a coherent system
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this perspective, we propose a novel approach where the entity has a world of simulation: it can simulate itself (using its own model of behavior) and simulate its environment (using its representation of other
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of these reusable packaging using IoT sensors and deep learning techniques embedded in the sensors. During the preliminary work, neural network models were developed to perform simple tasks using accelerometer data
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from centralized treatment plants. This model has improved sanitation and reduced pollution but falls short of addressing current challenges like rapid urbanization and climate change, including
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Numerical Study of Soil Remediation by Thermal Desorption with a Focus on Industrial Decarbonization
, coupling fluid flow and heat transfer phenomena with desorption kinetics. The developed model will be informed by operational data from real industrial sites and will incorporate literature data for common
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of demonstrating a system where a user can request a dish in natural lan-guage, leveraging large language models (LLMs). In response to the growing shortage of caregiving personnel, this work proposes innovative
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insufficient for modeling the long-term evolution of attacks, correlations across multiple data sources, and causal relationships between entities. A central objective is to bridge the gap between automated