133 cloud-computing-"https:" "https:" "https:" "https:" "https:" "St" positions at ETH Zurich in Switzerland
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COMPAS XR framework developed at ETH Zürich. Project background The successful candidate will work at the intersection of computational design, XR, human-computer interaction, and robotic fabrication, with
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understanding of the aging of solid insulation under mixed-frequency medium-voltage stress, see https://doi.org/10.1088/1361-6463/acd55f for a relevant example research work of our team in this area. Profile
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Lugano and in Zurich. Project background As high-performance computing, AI, and cloud technologies continue to converge, CSCS is redefining how to design and deliver advanced computational services. Modern
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management policies to achieve energy neutrality and autonomous operation in long-term deployments. Edge–cloud integration and field deployment. Deploy and validate sensor networks on representative assets
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, deployments in the clouds or on our own servers. We’re now looking for a new team member to join our Software Development & IT team. Read on to find out if this could be the right fit for you! You’ll be working
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experimental-design principles, especially as applied to perturbation-effect estimation at both perturbation and gene levels. Bioinformatics workflow design (Snakemake/Nextflow) and HPC/cloud computing
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psychologists, neuroscientists, computer scientists, clinicians, and data scientists across the Singapore-ETH Centre (SEC), the National University of Singapore (NUS), and Nanyang Technological University (NTU
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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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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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operations that are yet to be fully understood. In this context, it is evident that the operation, control, and planning of power systems will soon be pushed to their limits. Therefore, new computational