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it is to be expected that the environment contains obstacles or is partitioned in a way not apparent when starting the coverage plan. Classic “Coverage Path Planning” algorithms are restricted in
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of algorithms based on artificial intelligence, since, to fully exploit the potential of AI, algorithms must be fed with data. This research project will examine these issues by focusing on three main areas
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, and systematic evaluation of results. Objectives: Development and application of artificial intelligence algorithms for different use cases in the energy sector, e.g., forecasting of renewable energy
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on research topics related to AI in Education. We are looking for a candidate with prior research experience in both AI models/algorithms and learning sciences/education background. This will help in
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 2 months ago
(PETs) and privacy assessment functionality based on MAGNET scientific advances By default all developed software will be open-source. Tasks may include developing algorithms, e.g., cryptographic
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are seeking a Research Scientist specializing in Machine Learning, Data Science, Data Harmonization, and Synthetic Data Generation to lead the integration, standardization, and privacy-preserving algorithmic
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to publications in top-tier international conferences and journals, as well as real-world implementations. The role includes designing novel algorithms, building robust software systems, and collaborating with
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. The successful candidate will assist in developing novel algorithms and integrating them into robotic platforms, helping to push the boundaries of embodied intelligence in both research and practical deployment
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support the development, simulation, testing, and implementation of collaborative control algorithms for multi-agent robotic systems, under the guidance of the PI and senior researchers. The work will first
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persist across participants, and retraining from scratch is often computationally infeasible at scale. In this project, you will develop the next generation of federated machine unlearning algorithms