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downtime and operational costs. Traditional condition monitoring approaches often face challenges in accurately detecting early-stage faults, especially in the presence of highly impulsive signals
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learning surrogates. In order to expand from the boundaries of the learning space, effectively generalize knowledge and extrapolate behaviour for unseen conditions, unseen locations and even unseen turbines
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still uncertain how forest structure is impacted by disturbances (locally) and how we can detect and monitor various levels of disturbance regimes using spaceborne satellite data (globally). This PhD
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nematode community to N mineralization and N2O emissions in realistic soil conditions. In this project, we will set up unique multitrophic experiments controlling for the presence of specific trophic groups
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run-off, sea dumping operations, mining, explosions, and oil seepages—enter the marine environment. Maintaining healthy seas can only be achieved by developing an innovative monitoring strategy and