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done for two case studies, namely Western Scheldt and Wadden Sea. To facilitate knowledge exchange and the learning process, interactive workshops will be organized on location (Western Scheldt and
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Welcome to Maastricht University! You just finished your PhD trajectory and looking for the next step in your academic career? Your interests lie in the field of machine learning techniques
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your academic career? Your interests lie in the field of machine learning techniques, particularly artificial neural networks, and deep learning? And you would like to continue your research
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for reasoning, on efficient and explainable machine learning for extracting and structuring information from large datasets, and on combining the two in neuro-symbolic AI.
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, solvent-based recycling process for complex plastic waste streams such as multilayer packaging and e-waste, while Exergy will develop the digital-twin and machine-learning tools that make the process
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cardiovascular care. Within the consortium, TU Delft contributes expertise in cardiac mechanics, soft tissue modeling, growth and remodeling, machine learning, and uncertainty-aware model personalization. As a
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measurement techniques and PIV. Familiarity with optics, lasers, image processing and statistical data analysis. Familiarity with flow modelling techniques (CFD) or machine learning for fluid flows. Aptitude
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postdoctoral researcher, you will lead the human-computer interaction side of the project. You will investigate how everyday athletes and coaches currently use tracking and feedback technologies, design and
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processing and statistical data analysis. Familiarity with flow modelling techniques (CFD) or machine learning for fluid flows. Aptitude for team work and excellent communication skills in spoken and written
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and high-speed microscopy with AI and machine learning to form stable liposomes from libraries of (novel) phospholipids that can robustly encapsulate cell-free gene expression systems. You will then