183 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Helmholtz-Zentrum-Hereon" positions at ETH Zurich
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) project, starting May 1st. This role sits at the intersection of applied machine learning, natural hazards, and snow/avalanche physics. The project is named Towards high-resolution, intelligent
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processing times continue to limit its clinical reach and robustness. Recent advances in machine learning, particularly deep learning and physics-informed methods, offer transformative opportunities
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of machine learning, AI, and cancer genomics. Our lab develops novel machine learning methods to understand biological systems and cancer, with a strong focus on genomics and translational impact. We work in
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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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, Computer Vision, Control Systems, Deep Learning, Digital Humans, Earth Observation, Educational Technology, Efficient AI, Explainable AI, Graph Representation Learning, Haptics, Human-Computer Interaction
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Master’s degree in Computer Science, AI, Machine Learning, Mathematics, Electrical Engineering, or a closely related field; or Master’s degree in Medicine (MD) with strong Python skills and some ML
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knowledge and technology from research to Swiss machine, electrical and metal industries. The research group Laser Material Processing at inspire offers in collaboration with the Advanced Manufacturing
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the power of both classical and quantum computing resources? How can we exploit or take inspiration from quantum physics to develop cutting-edge machine learning? Your work will encompass a diverse array of
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methods. Contributing to the development, adaptation, and application of machine‑learning models tailored to RODI data (in collaboration with project partners). Designing and implementing an innovative
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space applications. We combine theory, physics-based simulations, machine learning, and autonomous workflows to understand and design materials that can perform under conditions where conventional