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Field
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mandatory core focus, the PhD position allows room for the individual research interests of the applicant to shape specific aspects—whether in modeling strategy, applied machine learning methods
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or Cloud computing and machine learning techniques? You stand out from your peers because of strong commitment and independent work? You are a team player and communicative (excellent oral and written
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the individual process parameters on the target properties and develop predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy with defined microstructure
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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frequent cloud contamination. This scale mismatch prevents a coherent representation of radiative–thermal processes at the urban scale. This PhD will develop physics-informed deep learning models for data
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identification and machine learning. The key challenge is striking a balance between, on the one hand, modelling the physical, dynamic and nonlinear behavior of the components with sufficient physical accuracy
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management, and machine learning approaches for process monitoring and control For this function, our Brussels Humanities, Sciences & Engineering Campus (Elsene) will serve as your home base.
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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17 Oct 2025 Job Information Organisation/Company ETH Zürich Research Field Chemistry » Other Engineering » Chemical engineering Engineering » Computer engineering Engineering » Electrical
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authorities. École des Ponts ParisTech, in accordance with its strategic plan, develops a long-term research activity in the field of Machine Learning and Computer Vision. The IMAGINE team is a renowned