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, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from nonlinear control and optimisation
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There is an increasing demand for infrastructure services while, at the same time, infrastructure networks reach capacity thresholds. Extending and upgrading infrastructure is challenging and
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? The site could be temporarily unavailable or too busy. Try again in a few moments. If you are unable to load any pages, check your computer’s network connection. If your computer or network is protected
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of improved workflows in field studies These tasks will be carried out within the Marie Skłodowska-Curie Doctoral network METAMIC 3 - Metaproteome-based leveraged microbiome management in the context of One
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internships at KU Leuven (Prof. Rodolphe Sepulchre) and at TU Delft (Prof. Charlotte Frenkel) Participate in yearly retreats organized by the doctoral network participants Support the dissemination of software
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to cascading hazards, particularly NaTech (Natural Hazard Triggering Technological) events. REUNATECH is a Horizon Europe Marie Skłodowska-Curie Doctoral Network that aims to educate and train the new
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), Deep Neural Networks. Probabilistic Machine Learning and Time-series Analysis. Industrial applications of AI (energy, process industry, automation). Software development experience in teams. Programming
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). The candidate should have hands-on experience developing state-of-the-art machine learning models, particularly deep neural networks (experience with graph neural networks is highly valued). Their background
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, particularly NaTech (Natural Hazard Triggering Technological) events. REUNATECH is a Horizon Europe Marie Skłodowska-Curie Doctoral Network that aims to educate and train the new generation of Doctoral
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problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control