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. Candidates should provide proof of excellence in teaching. They should show expertise in their specific area and experience in Data Science and/or Software development, including academic publications and
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 5 days ago
, located at Inria Paris and École Normale Supérieure (ENS). The team conducts research in various aspects of quantum information theory, including quantum error correction, quantum algorithms, and the
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control and energy management strategies, including centralized / distributed control approaches, for ESS coordination and ancillary service delivery. Develop optimization algorithms and Al-based methods
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Alcotra RESIL-AV project, which will start on September 1, 2025, and run for a total duration of three years. The objective of this Franco-Italian project is to develop a common approach to a shared
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work will be organized around the following areas: 1. Bee detection and tracking: Development of computer vision algorithms to identify and track each bee from high-resolution images, while
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for simulating such complex geometries. For example, the memory and computation time required become prohibitive with standard “black-box” finite element methods. The objective is therefore to develop a dedicated
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interdisciplinary, and together we contribute to science and society. Your role Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms
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, it has matured into an established research community seeking automatic, computerized processing of 3D geometric data obtained through measurements or designs. The following developments have shaped
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proof of excellence in teaching. They should show expertise in their specific area and experience in Data Science and/or Software development, including academic publications and contributions
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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 8 hours ago
behaviours. Various methodologies have been developed, including physics-informed ML approaches that use numerical modelling to create synthetic datasets (e.g. Tristani et al., 2025). Additionally, approaches