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problems. This level of complexity increases when considering the multi-period operation of the system. These are difficult to solve using traditional strategies, so in recent years machine learning
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/technical challenges Project FITNESS will build upon and extend state-of-the-art methods [1], [2] recently developed within the team, showing to outperform existing, machine-learning based approaches in
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on individualised data; (2) to speed up FE model computation through machine learning prediction, in order to make it usable in clinical routine; (3) to conduct experimental validation of FE prediction results, in
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informing users and the network of new settings. The goal is to define an adaptive multicast framework leveraging error correction and machine learning to optimize parameters in real time [8]. 1.2. Scientific
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interdisciplinarity, blending machine learning, computational creativity, and musicology. It bridges AI methods—like generative models—with musical structure, theory, and cultural contexts, emphasizing data-efficient
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20 Feb 2025 Job Information Organisation/Company IMT Atlantique Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country France Application
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. T. (2022). Quantitative brain morphometry of portable low-field-strength MRI using super-resolution machine learning. Radiology, 306(3), e220522. [Winter2024] Winter, L., Periquito, J., Kolbitsch, C
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, machine learning, remote sensing, and oceanography to tackle the challenges of capturing and interpreting complex geophysical processes. 1.5. References [1] Torres, R., Snoeij, P., Geudtner, D., Bibby, D
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highly interdisciplinary, integrating network engineering, IoT device management, machine learning, and cybersecurity. It blends protocol optimization (Coreconf/YANG) with LLM-driven automation, enhancing