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This project aims to advance representation learning in cybersecurity by developing deep learning architectures capable of extracting high-level, structured, and semantically meaningful representations from
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, traceable industrial packaging that can be shared between manufacturers, we are recruiting a deep learning Post-doctoral researcher in our Mathematical and Electrical Engineering (MEE) Department. Using
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: Required: • MSc (or equivalent) in: Computer Science, Cybersecurity, Machine Learning, or related field • Strong background in: machine learning / deep learning, mathematics (probability, linear algebra
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automated configuration mechanisms based on fingerprinting and machine learning to ensure traffic analysis remains faithful to the behavior of the monitored machines. Finally, you will validate your solutions
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environments (Gazebo, Unreal Engine, or Unity). You have experience in artificial intelligence (Deep Learning, PyTorch) or embedded systems (ROS2, FPGA/VHDL design). You are curious, show scientific rigor and
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++), Deep learning tools (PyTorch) Computer Vision tools (OpenCV, MeTRAbs) English scientific communication skills. LanguagesENGLISHLevelGood Research FieldComputer science Additional Information Benefits
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. Panagiotis Papadakis and Associate Prof. Mihai Andries Keywords: Deep learning, event cameras, human skeleton, pose estimation, action recognition Where to apply Website https://imtatlantique.fillout.com