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We are offering a PhD student position in machine learning (ML) theory, focusing on new methods for training models with a limited amount of data. The student will be a part of a new NEST initiative
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.” In this role, you will develop advanced methods to estimate rail roughness and defects based on onboard vibration and sound signals—contributing to a quieter, more reliable, and cost-efficient railway
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long-term, and most often global, perspectives on future renewable fuels for transport. We seek to rigorously analyse the feasibility of energy transitions, utilize empirical as well as estimated data
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