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traffic demands increase, there is a growing need for innovative methods to continuously assess track condition and predict deterioration. This PhD project addresses this challenge by developing a novel
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, including efficiency, fairness, reliability, and sustainability. Despite recent advances, existing mathematical models often fail to jointly capture these aspects and trade-offs, limiting their ability
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are looking for a motivated and talented PhD candidate to join a unique interdisciplinary project at the intersection of machine learning and formal methods. Information Machine learning models deployed in real
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interpretation and prediction of structure-property relationships. https://sustainablepolymersynthesis.com/ Interested? Want to know more about this position or what it’s like to work at our university? Reach out
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mental models, cognitive maps, and cognitive graphs. These approaches have provided important insights into how people perceive locations, learn route layouts, and understand spatial relations. However
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states, study their persistence and transitions, and examine whether such attractor states predict clinically relevant outcomes such as relapse, comorbidity burden, symptom severity, and functioning. In
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quality, particularly in controlled environments such as greenhouses and vertical farms. By integrating plant physiology, modelling, and data-driven approaches, the group aims to predict plant performance
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predictive reliability of advanced power electronic modules and systems. Location will be in Delft, as a team member of ECTM, in close collabrations with NL and EU industrial partners. Job requirements MSc
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, an essential but as yet unpredictable property that allows cell culture establishment. Besides using Arabidopsis as a model species, the focus will be on cocoa (Theobroma cacao) as a socially and economically