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trustworthy climate information from large-scale geospatial, satellite, reanalysis, and climate model datasets Advanced physics-aware machine learning for kilometer-scale climate process representation
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. You will operate as a player-coach: driving high-value partnerships end-to-end yourself while building pragmatic structures, processes, and the team setup needed to scale. You should be equally
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Actively scout and screen entrepreneurial talent, ensuring alignment with our community’s standards and needs Manage the operational process of onboarding new startups to the ETH AI Center – from first
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the North Atlantic salinity relative to AMOC variations, and interpreting them with the aid of process models and experiments with tracers in atmosphere-ocean general circulation experiments. Job description
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In this role, you will support the establishment and day-to-day operation of the ETH Swiss GeoLab. A key focus lies in providing high-level administrative and executive support, including managing
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The Complex Materials group at ETH Zurich translates the science of materials processing into societally impactful technologies through student entrepreneurship and interdisciplinary collaboration
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range of topics related to imaging with geophysical data. Our research focuses on mathematical methods for processing, imaging, and inversion of geophysical data, the physics of wave propagation, and the
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Computer Vision and Computer Graphics techniques to digitize human avatars and garments in 3D. Within this project, your role is to advance our existing algorithms that reconstruct 3D garments from multi
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campaigns . Our research group studies the crucial role of clouds and aerosols in the climate system, aiming to better understand how cloud microphysical processes drive both precipitation formation and the
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deposition process parameters govern film architecture (e.g., thickness, porosity, roughness, grain/particle connectivity, interfaces, adhesion, and pattern fidelity) and how this architecture ultimately