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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
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G. M. Silva, within the group of Prof. Roman Stocker, and focuses on the development and deployment of a new‑generation underwater imaging device to transform drift studies in riverine ecosystems. It
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develop predictive tools for mechanical failure. Our team is highly interdisciplinary and international, bringing together researchers with backgrounds in materials science, mechanics, and applied physics
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, biocompatibility or the ability to reach deep brain areas. To solve this problem, we developed Ultra-Flexible Tentacle Electrodes (UFTEs), consisting of fibers one order of magnitude smaller than hair (2.4 um x 7 um