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normalization and integration of data from different sources, defining appropriate strategies to deal with all ethical and privacy/security requirements; Contribute to the development, validation and integration
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the improvement of the wetting/during algorithm in TELEMAC2D, including the effects of vegetation. Modelling the SPM turbidity in 3D (using TELEMAC3D) in front of the Belgian coast, validated with 3D remote sensing
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this PhD project, you will investigate the co-design between event-based learning algorithms and neuronal hardware units with multi-scale time constants. The algorithmic methodology will exploit recent
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
quality. Secondly, different machine learning strategies based on traditional supervised learning techniques (e. g. random forest (RF), artificial neural network (ANN)) will be applied using the parameters
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language. - While our current digital infrastructure relies on classical networks, quantum networks are slowly becoming a reality. The coordination algorithms that govern their operation are unlike those
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on classical networks, quantum networks are slowly becoming a reality. The coordination algorithms that govern their operation are unlike those employed in classical networks, necessitating novel verification
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of algorithms and digital neuromorphic hardware is an additional avenue for enhancing the efficiency of the methods. In this context the research will explore digital, event-based implementations
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. This is because experimental techniques to solve structures of protein complexes favor more stable interactions with larger interfaces and because we lack efficient algorithms to compute similarity between
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sanitation industries. Working with our established industry partners, you'll implement your innovations in real operational environments, seeing your research make tangible difference while building
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optimization to find the optimal set of parameters that improve process performance and material quality. Secondly, different machine learning strategies based on traditional supervised learning techniques (e.g