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learning, deep learning, neural differential equations, diffusion models, flow matching, dynamical systems theory, control theory, model predictive control. You have excellent technical/computational skills
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-organising reaction networks and the emergent complexity in such systems form powerful reservoir computers capable of non-linear classification, times-series prediction and forecasting, on a par or even
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provide intuitive, human-interpretable explanations for complex model predictions derived from Earth Observation data, including high-resolution satellite and aerial imagery. You will engage in a
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properties of catalysts together with statistical methods to derive predictive models for selective catalysis. In a data-driven approach, an initial set of reactions is analyzed and used to establish such a
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materials, to aid design of novel more energy-efficient processing routes. The development of these digital twins requires reliable and predictive models for microstructure formation during steel processing
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weather prediction using Machine Learning approach (hybrid forecast). The app is also expected to be equipped with seasonal forecast for agricultural planning. You will co-design the short-, medium-, and
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to characterize the molecular properties of catalysts together with statistical methods to derive predictive models for selective catalysis. In a data-driven approach, an initial set of reactions is analyzed and
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. What will you research? The use of AI in the public sector is growing rapidly: from detecting fraud to predicting nitrogen emissions. These applications can speed up and objectify procedures, but also
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regarding the demand that will have to be met soon. This requires building robust models to predict future demand, making decisions under time heterogeneous uncertainty and adapting to the state
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predictive models and novel measurement methods that improve coating performance for corrosion protection, heat reflection and radiation shielding. You will collaborate closely with our industrial partners