204 structural-engineering "https:" "https:" "https:" "https:" "https:" "https:" "Multiple" "U.S" uni jobs at ETH Zurich
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knowledge and technology from academic research into the Swiss mechanical, electrical, and metal industries. The Machine Concepts research group at inspire AG is offering a position in the field of Industrial
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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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100%, Zurich, fixed-term The brain is a very complex system consisting of billions of neurons that interact with one another. Capturing this network activity at a single-cell level from multiple
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80%-100%, Zurich, fixed-term The Center for Climate Systems Modeling (C2SM) at ETH Zurich is a joint, interdisciplinary center linking ETH Zurich with partner institutions. It provides a technology
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The ETH Zurich technology platform NEXUS Personalized Health enables discovery and translational research for personalized health. We offer a broad range of expertise across Clinical Bioinformatics
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thinking with a structured, quality-focused approach to data and methods. Ideally, experience in one or more of the following: data engineering, building data-driven apps, computational linguistics, machine
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80%-100%, Zurich, fixed-term The brain is a very complex system consisting of billions of neurons that interact with one another. Capturing this network activity at a single-cell level from multiple
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for world class research in the field of robotic fabrication in architecture and construction. Job description We are looking for a highly skilled software engineer to work on the development of python
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stakeholders ranging from public health to finance, agriculture, and water management. By pooling competence from 20 leading Swiss research institutions across multiple natural and social science disciplines
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industrial partners to tackle advanced modelling, simulation, sensing, and data analysis challenges in engineering systems across sectors. Project background The COMBINE Doctoral Network aims to train a cohort