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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | about 6 hours ago
of material deposited, while maintaining the expected accuracy. Part of the activity will also involve implementing Artificial Intelligence (AI) methods similar to computer vision to facilitate this prediction
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need for graduate student services to provide technical and/or analytical support in the field of computer science and electrical engineering for a computer vision team, specifically for the Shipboard
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Science, or a related technical field Master's or PhD degree in Machine Learning, Computer Vision, or related areas will be advantageous Preferred Qualifications: Experience with biological/ecological
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solid Python skills. Interest in computer vision, representation learning, concept drift, Statistical Process Monitoring (SPC/SPM), active learning/DOE, MLOps. Curiosity, independence, and excellent
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record relevant to the topic - publications in top journals or conferences (e.g. computer vision (CVPR/ICCV/ECCV), machine learning (NeurIPS/ICML), or robotics (ICRA, IROS, RSS, CoRL; IEEE-TRO, IJRR
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23 Dec 2025 Job Information Organisation/Company Computer Vision Center Research Field Computer science » Other Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Country
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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, Optimization, Machine Learning, Reinforcement Learning, Computer Vision, and Pattern Recognition, as well as contributing to curriculum development. About NYU Abu Dhabi https://nyuad.nyu.edu/en/ NYU Abu Dhabi is
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-phd-positions/ . Requirements Top-ranked Master's degree in robotics, computer vision, system control, machine learning, mathematics, or a related field (background in any of the following); Being
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Engineering and Mechatronics. The Proposed PhD thesis topic: “Intelligent Diagnostics of Electrical Machines through AI-Enabled IoT Systems: Design of Custom Embedded Hardware and Protocol-Aware Architectures