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of technological innovation aimed at sup- porting farmers by alerting them of imminent lambing events. Its objective is to provide a reliable predictive system based on sensors and artificial
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screening to a predictive, rational design of absorption media (WP1) and to validate their efficiency in VOC capture, with a specific focus on emissions from the semiconductor industry. (WP2). The project
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 4 days ago
the prediction of vehicle flows, energy demand, and flexibility of electric vehicle fleets, with applications to energy and transportation systems. The work lies at the intersection of systems and control, data
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focused on exploration and development of AI models of auditory perception, towards a broader goal of understanding how the brain predicts and learns from human communication sounds such as speech and music
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models are deeply rooted in real-world biological data. The collaborative approach allows for the development of predictive models that bridge the gap between theory and experiment, with a focus on high
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on hospitalizations for RSV bronchiolitis. Brault et al, Lancet Child and Adolescent Health, 2024 Development of an ensemble model to forecast COVID-19 hospitalisations in France. Paireau et al, PNAS 2022 Estimating
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motivated postdoctoral researcher to develop and apply imaging-based and computational approaches to identify predictive nuclear signatures of cell fate. The project combines experimental and quantitative
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(CRC), Paris Scientific supervisors: Prof. Jean-Charles Nault Project: SIGN’IT 2025 – MIMIC: Multimodal multi-omics approach to predict response to immunotherapy in advanced hepatocellular carcinoma
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:this project pioneers a new paradigm of General Genome Interpretation (GenGI) models by combining DNA Large Language Models (DLLMs) with Deep Neural Networks to predict human phenotypes directly from Whole Exome
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responsibility of developing predictive tools based on machine learning for the analysis and interpretation of Raman vibrational spectra applied to battery materials. The successful candidate will design and