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constitute the core objective of the proposed PhD project. Expected contributions of the Thesis Model realistic multi-orbit/multi-operator SatCom scenarios; Design AI/ML-based prediction models for mobility
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools
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assignment of a research grant, with one position(s), under the project CENTRO2030-FEDER-02359500, title ENDOSWEET - Sugars and polyols generated endogenously as predictive markers of Type 2 diabetes
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University College of Medicine, our goal is to use the lens of metabolism to better understand and predict cancer progression. We use a combination of experimental and clinical data paired with computational
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fundamental physical model to understand the process of fire spread for wildfires, as part of the European Research Council grant FIREMOD: (https://cordis.europa.eu/project/id/101161183 ). This is a full-time
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infrastructure to support predictive analytics, recommendation, and dynamic pricing. Create pipelines and databases capable of aggregating and organizing information from multiple heterogeneous sources. O5
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geometries and process-induced defects demand new inspection approaches. The project combines modelling, sensor fabrication, experiment, and data analysis. You will work with a team of experts to develop
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time. In this project, we propose a method for identifying and classifying such emerging asynchronous trends. The goal is to be able to predict how a new emerging trend will develop using similar
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Starrydata2). The work will include the implementation of machine learning models (neural networks, random forests, SISSO), generative approaches for predicting crystal structures, the use of machine learning
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 29 days ago
intelligence is growing at a fast pace, the bulk of the world's computing power remains targeted at modeling and predicting physical phenomena, such as climate models, weather forecasting, or nuclear physics