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invites applications for a fully funded PhD position at ETH Zürich at the intersection of robotics, wearable sensing, signal processing, machine learning, and human-computer interaction. The goal of
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project aims to develop new methods for estimating blood pressure and quantifying flow inefficiencies using medical imaging, machine learning, and computational modelling. The doctoral candidate will
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both ETH Zurich and IBM Research Zurich, benefiting from the synergy between academic and industrial research. The topic of the PhD position sits at the crossroads of quantum computing, machine
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. By bridging machine learning, behavioural science, and clinical research, the project seeks to establish foundational methods for trustworthy agentic AI systems that can be deployed across diverse
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, indicators and survey information. The division combines macroeconometric modelling with data science methods for nowcasting, high-frequency indicators construction, machine learning, time series
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-informed neural networks (PINNs) and other machine-learning approaches build and extend our simulation environment, with a focus on performance, scalability and reproducibility apply your methods to real
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/nl/medewerkers/s-e-verwer) for more information on possible research topics. Your profile Master’s degree in computer science, mathematics, machine learning, cybersecurity, or related field. If you
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/nl/medewerkers/s-e-verwer) for more information on possible research topics. Your profile Master’s degree in computer science, mathematics, machine learning, cybersecurity, or related field. If you
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/nl/medewerkers/s-e-verwer) for more information on possible research topics. Your profile Master’s degree in computer science, mathematics, machine learning, cybersecurity, or related field. If you
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/nl/medewerkers/s-e-verwer) for more information on possible research topics. Your profile Master’s degree in computer science, mathematics, machine learning, cybersecurity, or related field. If you