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learning with the physics of laser–matter interaction. Your developments will be directly validated through multiple experimental runs on state-of-the-art laser processing equipment. You will work closely
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interaction. Your developments will be directly validated through multiple experimental runs on state-of-the-art laser processing equipment. You will work closely with experts in material science, numerical
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The Faculty of Medicine of the University of Zurich invites applications for a Professorship and Chair of Pediatric Cardiac Surgery. The professorship is based at the University Children's Hospital
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. Empa is a research institution of the ETH Domain. The Laboratory for Advanced Materials Processing aims to be an international leader in developing and optimizing innovative 2D and 3D manufacturing
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Doctoral Candidate in computer vision and machine learning for developing novel deep learning method
Machine Learning (DM3L) Doctoral Candidate in computer vision and machine learning for developing novel deep learning methods for satellite-based tracking of global CO2 and NOX emissions of point sources 80
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Description Two PhD positions in atmospheric selenium research: field & lab analyses and process-based modeling We are seeking two highly motivated and curious PhD students to join the Inorganic Environmental
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infrastructure that supports world-class science in Switzerland. To achieve this mission, multiple specialized engineering teams must collaborate effectively, utilizing a dynamic set of processes and tools
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. Empa is a research institution of the ETH Domain. Empa's Laboratory of Biomimetic Membranes and Textiles is a pioneer in physics-based modeling at multiple scales. We bridge the virtual to the real world
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. Empa is a research institution of the ETH Domain. In our research group, we transfer membrane and encapsulation strategies from academia to industry. Solution-based processes like electrospinning and
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, we collect data through biological monitoring, environmental DNA methods, remote sensing, and field sampling, and use these data to answer questions with statistical and process-based models