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systematic phases: first, establishing a robust data foundation; second, designing a modular and open digital platform; and third, developing a predictive maintenance application as a proof of concept
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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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phases of matter with unprecedented resolution and sensitivity. We aim to achieve this goal through the confinement of charges and photons in reduced dimensions. We welcome candidates with strong
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