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LMPS - CNRS - CentraleSupélec - ENS Paris-Saclay | Gif sur Yvette, le de France | France | about 8 hours ago
localized at the level of anchoring devices such as clamps or sleeves. In this context, RTE (Réseau de Transport d'Électricité) deploys tools aimed at estimating the residual lifespan of conductors based
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methods is desired. 8. Experience with eye-tracking methods is desired. Preferred License: Yes If yes, what is the preferred licensure/certification?: valid US driver’s license Preferred Computer
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(estimation filter) methods, while preserving the convex character of the optimization problems to be solved. An alternative path to consider will be the use of convex relaxations. As the expected contributions
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. Desirable Criteria Experience implementing machine learning or deep learning models (e.g., neural networks, probabilistic learning methods). Knowledge of state estimation techniques, such as Kalman filters
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intelligence, and multimodal learning. The main objective of this position is to develop novel generative AI methods for computer vision applications, with a particular focus on Diffusion Models and Vision
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090,98 paid by bank transfer (according to FCT values table: https://www.fct.pt/wp-content/uploads/2026/03/Tabela-de-Valores-SMM-202… ), supported though PAD no. C69621 and C69622. 8. SELECTION METHODS
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systematically improve the quality of production processes and final products. Continuous improvement must be implemented as a managed and ongoing system supported by modern quality management methods and computer
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spectrometry. (Will consider additional related post high school education in lieu of experience) Required License No If yes, what is the required licensure/certification? Required Computer Applications
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Positions in the Department of Electrical & Computer Engineering for the Fall 2026 semester. These positions are open to McGill University Graduate students only. This position requires in-person work and is
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evolutionary). The project aims to approximate a Boltzmann distribution associated with an objective function that is difficult to optimize in order to solve complex optimization problems. This probabilistic