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travel behaviour data or urban mobility patterns Good German language skills (at least B2) Experience with collecting own data (e.g. questionnaires; measurements) Experience with developing networks with
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Preprocess, annotate, and manage a rich multimodal dataset, applying both qualitative and quantitative analytical methods to model clinician attention, verbal reasoning, and documentation behaviour Develop and
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. The group typically takes over work as systems mature from development into real-world use, and it also picks up operational priorities that arise across NEXUS. In line with our values , ETH Zurich encourages
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that make biomedical and clinical data usable in practice. The team currently has 5 members and supports a broad portfolio, ranging from internal tools and research platforms to applications developed
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interested in applied machine learning and computer vision at the intersection of research and industrial deployment. Job description Develop and implement state-of-the-art computer vision algorithms
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affect technology adoption, industrial development, policy design, and its socio-technical and political feedback effects. The project is embedded within ETH Zurich’s new Einstein School of Public Policy
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frames). Project background The work focuses on data-driven generation of structural systems. You will be involved in developing, experimenting with, and evaluating machine learning models that help
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to work at the interface of quantum optics, quantum information science and quantum many-body physics. Led by Prof. Wenchao Xu , the EQE group develops programmable quantum systems based on neutral atoms
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and develops a blueprint for actionable climate research worldwide. NCCR CLIM+ broadly communicates and shares knowledge, and trains a new generation of experts with the necessary domain and
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engaged in development of electrochemical sensors detecting environmental pollutants, providing real-time information for effective management. Past and current work includes electrochemical sensors