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these challenges by: Developing predictive workload, lead-time estimation, material planning models to capture the high variability in HMLV environments using hybrid AI (combining machine learning, feature-based
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complex, high dimensional and high-volume datasets. Uses data preparation, modeling and predictive modeling, analysis, processing, algorithms, and systems. Applies knowledge of statistics, machine learning
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to this research line, planning protocols, overseeing data collection, facilitating communication between teams, and ensuring ethical and regulatory compliance. Implement data-analysis models to predict cognitive
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Infrastructure? No Offer Description This project is part of the European ERC Synergy project Karst https://erc-karst.eu/ , which aims to develop a predictive flow model for an entire karst network. We will
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Centre National de la Recherche Scientifique (CNRS) | Saint Aubin Routot, Haute Normandie | France | about 8 hours ago
inverse modelling in geosciences. (https://www.ipsl.fr/ ) Task description for your Individual Research Project (IRP) Problem Definition: In order to account for the chemistry occurring in the rocket plume
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natural and human disturbances through climate-smart forestry startegies, based on observations and predictive models. Where to apply Website https://unimol.concorsismart.it/ Requirements Additional
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in the prediction and modelling of extreme flood events? Do you want to understand how
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predictive modelling; Bioinformatics and Knowledge Graphs (visualization and reporting); AI-based data integration across cohorts (with federated machine learning); Contribute to ongoing projects, such as: o
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Your Job: You will be a member of a consortium of leading research institutes and an industry partner. Your task is the build-up of a predictive model for tandem cell stability. Your tasks in detail
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of the SU(N) Fermi-Hubbard model and its low-temperature phases at the microscopic level. Share this opening! Use the following URL: https://jobs.icfo.eu/?detail=1003