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, you are involved in research activities where Die to wafer bonding is required (3D integrated systems, image sensors, photonics, biomedical devices, quantum computing,...). More specifically, you will
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generative AI algorithms and translate them into intuitive explanations. Interest in cyber-physical systems (CPS) and eco-cognition modeling. Good understanding of mathematical optimization techniques
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or PyTorch. Interest in explainable AI and contributing to explainability repositories for trustworthy, auditable algorithms. Experience or interest in cyber-physical systems (CPS), eco-cognition, and
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limited to): O-RAN based architectural integration of 5G/6G Terrestrial/Non-Terrestrial and Wi-Fi, development of advanced algorithms and optimisation techniques to enhance the performance and efficiency
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and Delivery: Design and develop training programs on Data Science and AI topics, including machine learning algorithms, data visualization, and statistical analysis. Provide foundational sessions about
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integration of 5G/6G Terrestrial/Non-Terrestrial and Wi-Fi, development of advanced algorithms and optimisation techniques to enhance the performance and efficiency of the integrated RAN, spectrum management
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functionality. Your work will involve designing advanced algorithms that efficiently utilize UWB signal features (RSSI, channel impulse response, phase and amplitude data, Doppler maps,..) to support both high
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reinforcement learning for flexibility exploitation, and design of AI-based energy management algorithms to coordinate individual and combinations of flexible loads. These algorithms should cater for large asset