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knowledge of process systems engineering. The position aims to advance physically consistent and predictive thermodynamic modeling, including the integration of advanced machine learning methods, to support
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on the linguistic analyses provided; o Evaluating the results of the prediction and classification models developed by Loria. Praxiling is a Joint Research Unit (UMR 5267) under the joint supervision of the CNRS and
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W3 Endowed Professorship for “Hemodynamic Modeling in Atherosclerosis- (f/m/d) KSB Foundation W3 end
clinical application. The focus is particularly on photon-counting computed tomography (PCCT), 4D MRI flow imaging, and AI-supported analysis and modeling methods (e.g., CT-FFR, predictive software models
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French National Research Institute for Agriculture, Food, and the Environment (INRAE) | Villenave d Ornon, Aquitaine | France | about 2 months ago
be to develop predictive models dedicated to the ecological transition of agriculture. The project extends the understanding of links between metabolism programming and trade-offs with plant
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broad range of topics: from model-predictive building control and community battery integration to wind farm optimisation and multi-decade investment planning, we support clever algorithms and data
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approaches capable of guiding experiments, interpreting results in real time, generating predictive models of materials synthesis processes, and refining experimental strategies under a Human-In-The-Loop
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)—to enhance decision-making in dynamic environments. ML predicts load variations and failures, SDN enables centralized resource management, and NFV supports flexible service deployment.This thesis project
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speech processing, a research question that is rapidly gaining in importance. The project is centred on the hypothesis that the cerebellum conveys predictions about upcoming speech sounds to the neocortex
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model predictions with biological knowledge and external data sources. Work closely with academic partner groups and the Innovation & Business (I&B) team to align technical development with biological
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: Textual Prediction of Survival (LLM classification & Attention Modelling) This project develops a model to predict patient survival by analyzing heterogeneous clinical documents. Unlike traditional methods