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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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Electrical Engineering (or equivalent), have a solid mathematical background (e.g. in control theory and optimization) and have taken specialized courses in at least one of the following disciplines: advanced
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increasingly complex networks. By deploying and advancing techniques such as machine learning, graph-based network analysis, and synthetic data generation, the project tackles key challenges in anomaly detection
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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interdisciplinary research and training program. The objective of the open PhD position is to advance current over-the-air-computing (AirComp) approaches for federated and graph-based Embedded AI to account for
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should have strong digital signal processing and mathematical backgrounds evidenced by grades and/or prior publications. Additionally, the candidate should have expertise or strong interest (evidenced by
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29 Aug 2025 Job Information Organisation/Company Vrije Universiteit Brussel (VUB) Research Field Computer science » Other Mathematics » Applied mathematics Mathematics » Computational mathematics
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geotechnical engineering, civil engineering, geological or environmental engineering, energy engineering, mechanical engineering, or geosciences. Strong skills in mathematics and programming are considered
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: The successful candidate will receive interdisciplinary training in theories and methods for the study of the neuronal correlates of the adaptation to accented speech. This includes many network-wide