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at ETH Zurich and associated with the ETH AI Center. We are an interdisciplinary group at the intersection of chemistry and computer science. Our mission is to accelerate chemical discovery using digital
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40%-60%, Zurich, fixed-term SwissChips is a multi-institution research initiative in the areas of chip design, microelectronics, and semiconductors. For this initiative, we are looking for a project coordinator and communication manager to support the Director, the Project Management Office,...
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computer skills (MS Office, SAP, etc.) enable you to work efficiently Experience in the areas of event management and communication, and an affinity for technical applications and web CMS With your
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We are seeking a highly motivated and interdisciplinary Postdoctoral Researcher to join our team in developing a cutting-edge nutrient prediction platform. This project integrates machine learning with solid-state fermentation (SSF) using filamentous fungi to optimize nutrient profiles in food....
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We are supported by the Wyss Zurich Translational Center (Wyss Zürich), a unique accelerator program, which is embedded into ETH Zürich and University of Zürich and addresses the booming fields
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on Human Factors in Computing Systems, Lancet Digital Health, npj Digital Medicine). You will also be involved in teaching activities.
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the data and AIXD results Carry out standard tasks of debugging and documentation of the AIXD toolbox Profile You are a developer with a BSc or MSc in Computer Science or related fields, with proven
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research assistant position in Development Economics. The starting date is the 1st of October for 6 months. This is a position to get some research experience between a Master’s degree and a PhD program. Job
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afterwards. You will work closely with our research team to implement a new version of our RAG-based chatbot. Profile The ideal candidate will be a computer or data science student, or a student with extensive
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Emulators of Stochastic computational models"), funded by the Swiss National Science Foundation (SNSF). The project aims to significantly advance the state-of-the-art in uncertainty quantification (UQ) by