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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
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Your job As PhD candidate, you will be part of the project SHIELT – Shelf-life for plant-based meat alternatives. This project aims to develop predictive microbiology and risk assessment tools
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advanced operational strategies, such as model-predictive control, tailored to dynamic prosumer energy demand. Foster collaboration: Work closely with industrial and research partners, including CENAERO
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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 conditions. This
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, optically-pumped magnetometers, to understand how early learning develops. You will address how caregivers’ behaviour influences infants’ learning and how early differences in learning predict language and
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often inaccurate and costly. This process is long, expensive, and high-risk, with animal testing traditionally used to predict efficacy and safety for humans. However, animal experiments often fail
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throughout a day are uncertain, as they depend on hardly predictable weather conditions. This uncertainty increases the volatility of short-term energy prices, and thus makes it much more challenging to make