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sources, such as wind and solar. As a consequence of this shift, the amounts of energy that are traded at the short-term markets throughout a day are uncertain, as they depend on hardly predictable weather
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analytics (statistical models, machine learning, uncertainty quantification) to monitor and predict cycling travel conditions from various perspectives (safety, crowding, travel time, comfort, etc
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Wetsus - European centre of excellence for sustainable water technology | Netherlands | about 5 hours ago
can be more predictable. A series of projects dedicated to inspection techniques, is being executed in the Smart Water Grids research theme. In the past, this has already led to multiple spinoff
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Welcome to Maastricht University! Are you fascinated by how the brain predicts and adapts to the world
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to predict molecular subtypes in bladder cancer. Ultimately, the project seeks to identify novel therapeutic targets and validate these using bladder cancer organoids. You will be the first to create
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Wetsus - European centre of excellence for sustainable water technology | Netherlands | about 5 hours ago
microbial communities into function-related groups, and to generate predictive tools for linking specific microbiomes to defined soil functions. Your assignment You will identify the key soil functions
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want to contribute to the next level of self-driving labs? Are you excited about the application of high-throughput experiments to train AI tools to predict properties of complex mixtures? Then join our
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and accurately after surgery to measure and evaluate patients’ recovery progress, timely detect and even predict clinical adverse events like delirium, cardiac arrhythmias and pneumonia. In this project
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’ recovery progress, timely detect and even predict clinical adverse events like delirium, cardiac arrhythmias and pneumonia. In this project, the University of Twente (Biomedical Signals and Systems group
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physical accuracy and predictive capability by employing state-of-the-art methods for the following two modelling approaches: reduced-order models (ROMs) and input-output models derived from high-fidelity