277 structural-engineering-"https:"-"https:"-"https:"-"https:"-"University-of-York" positions in Switzerland
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Ph.D. Position in Organic Chemistry, Polymer Chemistry, and/or Sol–Gel Chemistry & Materials Science
Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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, μSR and other techniques. Geometric frustration in quantum systems leads to a tight competition between qualitatively new collective spin states, such as topological structures, quantum spin liquids
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* ETH Zurich – Where the Future Begins! As one of the leading international universities for technology and the natural sciences, ETH Zurich is well-known for its excellent education, ground
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. Empa is a research institution of the ETH Domain. We offer an opportunity to join an exciting project at our Structural Engineering Laboratory , within the Advanced Structural Materials and Systems (ASMS
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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Required Experience: PhD in Geodesy, Geomatics, Aerospace Engineering, Signal Processing, or a related field Proven experience in GNSS data analysis and processing Very good programming skills (e.g., Python
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Science at the ETH Zurich Institute of Environmental Engineering, with expertise in water chemistry assessments in forested ecosystems. The Silviculture group is part of the Chair of Forest Resources
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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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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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