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). This domain adaptation is crucial to ensure the generalization of the model to different types of sensors and environmental conditions. This aspect could notably be addressed by implementing graph-based
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 6 days ago
of hybrid modeling frameworks for electromobility, combining physical models, graph-based representations, and data-driven approaches. It aims at integrating large-scale mobility data to improve
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Post-Doctoral Research Visit F/M Postdoctoral position in web security, privacy, and online tracking
Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 1 day agoopaque tracking techniques (e.g., server-side tracking, identity graphs...). Simultaneously, the development of AI and LLM is having a tremendous impact on the web by modifying its structure to better suit
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prediction of gene perturbation effects for drug discovery. The successful candidate will play a leading role in developing gene perturbation models that combine foundation models (FMs) and graph neural
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Garcin. This comparison will be carried out from theoretical (emergence, economics, gravity, spatial interactions, graphs, urban form), methodological (robustness, error propagation, discrete choice
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3. These activities encompass the formalization of working practices and the creation of data corpora designed to be integrated into federated knowledge graphs. The researcher will work on documenting
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and implement Bayesian graph neural networks and convolutional neural networks as surrogates for high-fidelity biomechanical models Quantify and propagate uncertainty, and develop strategies for model
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language models to whole genome sequencing data - Develop algorithms and neural network architectures for the prediction of structured outputs (i.e. trees, graphs) - Implement and develop methods
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contribute to the development of a proof of concept obtained at University Côte d’Azur for accessing the content of a metabolomics knowledge graph (KG) with a large language model. It is Python prototype of a
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role Research in the general domain of stochastic analysis, with special focus on stochastic geometry, such as random fields, random graphs and related structures, limit theorems, stochastic calculus and