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The Faculty of Science and Engineering (FSE) provides teaching and research across a wide range of disciplines, from physics and biology to artificial intelligence, mechanical engineering, and
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technologies based on a digital twin. The digital twin will combine information from the physical structure with models and monitoring data to assess its current structural state and predict its remaining
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pose estimation algorithms. The models and algorithms you develop will be part of open source and data repositories affiliated with the broader research program and TU Delft’s commitment to Open Science
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) and experience in data analysis and computational methods. Familiarity with molecular biology techniques. Excellent written and spoken English skills. Ability to work effectively in a collaborative
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of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection
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The Faculty of Science and Engineering (FSE) provides teaching and research across a wide range of disciplines, from physics and biology to artificial intelligence, mechanical engineering, and
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Are you fascinated by how curiosity shapes learning in the classroom? Would you like to investigate how children seek information, explore and learn in real-world educational settings? If so, then
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explore new opportunities in semiconductor quantum technology and work to push the boundaries of quantum control in semiconductor qubits. The Veldhorst group is a dynamic group studying timely topics. Near
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Are you excited about the future of wearable healthcare? Join us to merge microfluidics and contact lens technology, developing smart lenses that enable controlled tear fluid collection and analysis
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geoscience, energy systems, materials modelling, fluid dynamics, and other scientific and engineering domains where data-driven models must interact with physical knowledge. Such problems raise fundamental