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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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Computational Fluid Dynamics (CFD) models; data-based models determined from training/calibration data by system/parameter identification and machine learning. The key challenge is striking a balance between, on
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simulations. Job Description Are you passionate about bridging computational modeling with clinical cardiology to solve real-world healthcare challenges? We're seeking a PhD candidate to develop innovative
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geospatial workflows on an abstract level, using purpose-driven concepts and conceptual transformations; develop AI and machine learning based technology to automate the description and modeling of data
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psychology) or data analysis (e.g., data science, statistics) Affinity with data science (e.g., complex statistics, machine learning or computational modelling) or willingness to develop relevant skills (in
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theory, and machine learning. They will have access to a fully equipped lab and benefit from collaborations within the ERC team and across TU Delft. There will be opportunities to present at leading
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researchers in soft robotics, control theory, and machine learning. They will have access to a fully equipped lab and benefit from collaborations within the ERC team and across TU Delft. There will be
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8 Sep 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Computer hardware Computer science » Digital systems Engineering
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questions. Given the uncertainties involved in food supply chains, we prefer candidates who have a background in (stochastic) optimization methods (e.g., machine learning, stochastic dynamic programming
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candidate for the research project Simplicial Type Theory. What are you going to do? A key step in the development of homotopy type theory was the construction by Voevodsky of a model of this theory in