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datasets, modelling approaches, and performance metrics; develop physics-informed and data-efficient machine learning models to predict sorbent behaviour from sparse and multi-modal experimental data; and
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requirements and focusing on data-value maximisation. This project will utilise innovative machine learning methods and tools from process systems engineering to simultaneously optimise product quality and the
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Max Planck Institute for Human Cognitive and Brain Sciences • | Leipzig, Sachsen | Germany | about 4 hours ago
TU Dresden or UCL may attend online. Application deadline See our website (https://imprs-coni.mpg.de/application-dates) for further information. Tuition fees per semester in EUR None Combined Master's
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