377 structural-engineering "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions in Switzerland
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- ETH Zurich
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- Swiss Federal Institute for Forest, Snow and Landscape Research WSL
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of synthetic biodegradable polymers. These materials-ranging from structural to water-soluble polymers-are designed for complete microbial metabolic utilization in their intended receiving environments (e.g
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the geological structures and potential reservoir Integrating extensive passive seismic recordings and borehole seismic data (including vertical seismic profiling, VSP) into the imaging and characterisation
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Lugano and in Zurich. For this position the preferred work location is Zurich, but it could also be Lugano. Project background We are seeking a driven software engineer to work at the intersection
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concepts into clear, engaging visuals - working closely with our engineering team to bring ideas to life. The scope of the work could be 60% for one project or with the right candidate and skill set extended
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, electrical engineering, a natural science, medical, or related field Experience in scientific research, ideally in the area of machine learning and/or data science Strong organizational skills and an
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. Scientific Background Stem cells are rare populations of cells that (in their primordial, i.e., ontological significance) serve as clonal founders of embryonic or adult somatic structures, while retaining a
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and engineering the structure, function, and dynamics of microbiomes across diverse biological and environmental systems. Several research groups at the Institute of Microbiology contribute to the NCCR
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The Paul Scherrer Institute PSI is the largest research institute for natural and engineering sciences within Switzerland. We perform cutting-edge research in the fields of future technologies
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of semiconductor devices. The aim is to predict these properties for arbitrarily large structures, at a DFT-level of accuracy. As a starting point, you will extend the large-scale equivariant GNNs we develop
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-project will be closely supervised by Prof. Hubert Pausch at ETH Zurich. The second candidate will focus on imputation and association testing. Approaches to impute structural variants into large mapping