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simulation models and enriched by operational equipment performance data. To this end, physics informed machine learning techniques will be used to bring model data and real data together in a Digital Twin
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We are seeking for a highly-skilled and self-motivated candidate with a strong mathematical background to do a Ph.D. on the fundamental aspects of graph machine learning with applications
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will explore the use of cutting-edge scientific machine learning framework that blends deep learning with physics-based techniques to achieve the goals of (i) identifying precursors and mechanisms
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Challenge: Analyse properties of biological systems Change: Develop novel control theory and machine learning methods to study natural systems and their robustness Impact: Produce new intelligent
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. Knowledge and experience in data science and machine learning. A good command of spoken and written English Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate
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performance, we will pioneer novel physics-informed machine learning algorithms to formulate an optical link performance map. This groundbreaking project comprises two PhD positions and one postdoc position
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on your interests and background, the focus will be more on the experimental fluid dynamics or the machine learning side. As a PhD student, you will be part of two vibrant teams of researchers with diverse
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, preferably but not necessarily on classification techniques and distributed radar systems. Knowledge or at least some interest in machine learning, preferably techniques for management/adaptation of systems
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but not necessarily on classification techniques and distributed radar systems. Knowledge or at least some interest in machine learning, preferably techniques for management/adaptation of systems
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are towards their learning objectives. The principal outcome of this work is the development of an intelligent platform designed to aid students in their programming education. Note: This PhD position is part