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Versatile Top-Down Patterning Technique for Perovskite On-Chip Integration. ACS Nano, 2025. State-of-the-art electronic device fabrication techniques will be applied during the project, including thermal
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sensing, computer vision or an equivalent field. You have experience in spatial modelling of habitats with machine learning and the use of large extent Earth Observation data. Experience in artificial
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running codes on HPC clusters). Knowledge of (or prior research) in robotics (e.g., ROS, forward/inverse kinematics), manufacturing (e.g., Additive or Subtractive Manufacturing), or computer vision/language
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modelling and AI/ML for the quality monitoring/control, at the end offering to the society novel nanostructured materials, their shape-forming and integration into devices. Your tasks We are seeking a highly
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. Empa is a research institution of the ETH Domain. Empa’s Laboratory Materials for Energy Conversion focuses on materials and device innovation for sustainable energy conversion and storage technologies
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. Utilizing a combination of experimental and computational approaches, we develop and characterize novel functional materials and devices driven by robust nanoscale quantum effects. We are currently seeking a
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are provided with a desk, access to IT and library infrastructure as well as a computer if required. Since the Collegium cannot provide laboratory infrastructure or studio space on site, early-career fellows can