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learning, particularly deep learning and physics-informed methods, offer transformative opportunities to redesign how data are acquired and reconstructed, and how physiological parameters are inferred from
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24 Jan 2026 Job Information Organisation/Company ETH Zürich Research Field Biological sciences » Biology Biological sciences » Other Chemistry » Analytical chemistry Chemistry » Biochemistry
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10%-30%, Zurich, fixed-term ETH Zurich I Space boosts space activities to establish ETH Zurich as the leading university in space research, education and entrepreneurship within Europe and beyond
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Scientist / Scientific assistant – Tree species detection using deep-learning Are you an ambitious data scientist with strong analytical and numerical skills, and expertise in geomatics, remote sensing, and
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methods for Federated Learning on resource-constrained networks. Your research within the project will contribute towards your doctoral degree at ETH Zurich. You will be supervised by Prof. Dr. Roger
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online calibration framework that leverages deep learning to intelligently fuse data from multiple sensors (IMU, cameras, eye-trackers) By training models on a high-fidelity digital twin and exploring
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. Implement high-performance C++ and Python modules for simulation, rendering, and data processing. Explore and integrate deep learning techniques into graphics and simulation pipelines (e.g., PyTorch, JAX
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23 Dec 2025 Job Information Organisation/Company ETH Zürich Research Field Architecture » Other Engineering » Civil engineering Engineering » Other Researcher Profile First Stage Researcher (R1
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challenges, exploring deep learning applications alongside traditional methods. Your responsibilities will include a combination of the following: Designing, developing, and maintaining data-analysis tools and
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Australia and #8 globally for Transportation Science and Technology (Shanghai Ranking 2025). IBLS maintains deep and enduring partnerships with industry, government, and international organisations