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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 13 hours ago
to improve the prediction of electric vehicle (EV) mobility patterns, energy demand, and state of charge (SoC) over time and space. The work will include the design of advanced modeling frameworks integrating
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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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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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quantitative and machine learning approaches ● Developing predictive models linking nuclear features to future cell fate ● Interacting with collaborators in imaging, computational biology, and developmental
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. - Conduct high-throughput serum proteomic analyses and integrate molecular datasets. - Validate candidate biomarkers in independent cohorts. WP3.2 – Integrated predictive modeling: - Develop integrative multi
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exploration. The MULTISPIN project aims to advance this field by establishing predictive models and assessing the circuit-level behavior of MFTJ devices based on van der Waals (vdW) two-dimensional (2D
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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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implement machine learning models dedicated to the prediction, interpretation, and quantitative analysis of Raman vibrational spectra, establishing explicit links between structure, local chemical environment
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. The functional relevance of these biomarkers will be investigated using both in vitro and in vivo models, as depicted in the publications of team. Selected Publications from the Team 1: Dousset L, et al
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, resilience and evolution of marine life to develop solid theories and predictive models of the relationships between marine biodiversity and ecosystem functions, which will in turn lead to improved economic