337 computer-programmer-"https:"-"FEMTO-ST"-"Inserm"-"AMOLF" "https:" "https:" "https:" "https:" "UCL" positions in Switzerland
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is to build efficient and robust computational tools for analyzing complex engineering systems. Applications include structural dynamics and other dynamical systems relevant to real-world engineering
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for further information) Scan of your validated UZH Card Letter of invitation or research plan Depending on the type of activity applied for, we require either a letter of invitation or a research plan. Letters
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interest in data-intensive systems. You bring a solid foundation in software or data engineering, typically developed through a Master’s degree or higher (e.g. PhD) in Computer Science or a related field, or
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evaluate prototypes together with industrial partners Profile Required experience CH/EU/EFTA citizenship or valid Swiss work permit PhD in Engineering, Computer Science, Robotics, or related field Strong
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operating and advancing the data platform, assist interdisciplinary projects that integrate multiple data sources, and use high-performance computing resources to manage and process large environmental
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-quantitative methods for decision support for sustainable innovation. Your tasks With the PhD work, we plan to adapt and advance the SSbD framework in the area of green electronics, with a special focus on bio
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& further information International Networking Close Menu Engagement back Overview PageEngagement Awards Knowledge exchange Action plan 2025-27 back Action plan 2025-27 Empowerment GROW Guidelines & Quality
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100%, Zurich, fixed-term The Computational Design Lab is an interdisciplinary research group at ETH Zurich, led by Prof. Dr. Bernd Bickel . We develop novel algorithms and next-generation
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80%-100%, Zurich, fixed-term We are seeking a talented Research Engineer with strong expertise in Computer Graphics, physically-based simulation, and high-performance implementation. In this role
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. Neuromorphic computing and ML deployment on digital and neuromorphic processors TinyML and EdgeAI and ultra-low-power inference for resource-constrained systems Techniques such as quantization, pruning