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are looking for a highly motivated and skilled PhD researcher to work on structural surrogates of offshore wind foundations through graph-based machine learning. Our goal is to perform full-structure
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are looking for a highly motivated and skilled PhD researcher to work on graph-based machine learning surrogates of wind energy systems. Our goal is to accelerate flexible fatigue load estimation
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platform. Initially, a black box deep learning approach will be implemented. However, due to the need for robustness, transparency, and explainability (e.g. for quality control across sectors), the research
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for anomaly Detection and diagnostics: Leveraging state-of-the-art machine learning and deep learning models for automated fault detection, classification, and time-till-failure prediction. This will involve
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FieldPhysicsEducation LevelPhD or equivalent Skills/Qualifications Who you are Ph.D. in Electrical Engineering, Physics, Photonics, or a related field with postdoctoral or industry experience preferred. Strong
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Information Systems engineering. The group conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities, and Machine Learning/AI 5G on organisations from
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information systems engineering. The group conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities, Machine Learning/AI, GenAI, and IoT/5G
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or altered behavioral responses in ASD models How these changes reflect underlying shifts in cortical circuit function You will work within the Bonin and Farrow Labs, which brings deep expertise in
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or altered behavioral responses in ASD models How these changes reflect underlying shifts in cortical circuit function You will work within the Bonin and Farrow Labs, which brings deep expertise in
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will be working in both groups (50% at UAntwerp, 50% at KU Leuven ) for the full duration of this project, who will be closely assisted by two postdoctoral fellows, based respectively at A-PECS (UAntwerp