146 computer "https:" "https:" "https:" "https:" "I.E" "UCL" uni jobs at ETH Zurich in Switzerland
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technologies (i.e. computing, data, algorithms, AI) in society. We are in particular looking for candidates who have interest and experience with STS and humanities pedagogy in the context of a technical
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and occurrence, many important phenomena, such as segregation, surface instabilities or jamming, i.e. the transition between a fluid- to solid-like state, are poorly understood. This project explores
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-facturing processes. In this internship, you will work on state-of-the-art anomaly detection methods using computer vision and time-series data, with a particular focus on multimodal data fusion for powder
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Department of Architecture (DARCH), i.e., digital fabrication, adaptive building components, or building envelopes? Then our 18-month fellowship on integrative research in occupant-centric daylighting and
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The MAS MTEC programme at ETH Zurich is currently undergoing a strategic transition. As part of this phase, we are seeking an Recruitment & Admissions Manager to strengthen and further develop
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backgrounds including biology, medicine, psychology, biochemistry, physics, engineering, computer science, and economics investigate fundamental questions about how the brain functions in health and disease
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diverse input pathways into engineered systems (i.e., wastewater) and natural terrestrial and aquatic environments (soils, rivers, lakes). The project will study enzymatic and abiotic breakdown
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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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, neuroscientists, computer scientists, clinicians, and data scientists across the Singapore-ETH Centre (SEC), the National University of Singapore (NUS), and Nanyang Technological University (NTU), the PhD student
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-scale geospatial and Earth system datasets, within the NCCR CLIM+ program. The role bridges climate science and AI, developing novel methods for climate data analysis, downscaling, and synthesis using