156 parallel-computing-numerical-methods-"Simons-Foundation" positions at ETH Zurich in Switzerland
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multiphoton microscopy, you will explore the molecular and cellular mechanisms of foreign body reactions. In parallel, you will collaborate with engineers to design and test microgels with tunable surface
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targeting biological pollutants, measurement of disease-related biomarkers, and study of organ-on-a-chip. We develop microfluid, optical and electrochemical methods in combination with microorganisms and
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novel method for autonomous design of 3D shapes fitting to the user body and optimizing the design to the desired assistance. Apart from actively shaping our group's research, the positions include
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FEniCS are a plus A keen interest in computational mechanics and in scientific methods and research in general Workplace Workplace We offer Your job with impact: Become part of ETH Zurich, which not only
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spatially aware predictive methods, tools will be developed to simulate the impact of system changes in selected scenarios, supporting the transition to a fully electric car-sharing service. These methods
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biology, or applied mathematics Documented experience in C++ programming and solid software engineering fundamentals Familiarity with numerical methods for solving PDEs (e.g., finite difference, finite
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the Department of Biosystems Science and Engineering of the ETH Zurich and by the Roche Pharma Research and Early Development (pRED). The programme focuses on development of new tools and methods to resolve
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100%, Zurich, fixed-term We invite applications for a PhD position in the field of quantum computing, to be advised by Dominik Hangleiter and co-advised by Renato Renner. In our group in Zurich
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. Scientific IT Services (SIS - a section with ITS) aims at bridging the gap between computational research and IT services and infrastructure provisioning. We are working closely together with ETH researchers
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experience in developing software for scientific applications, data analysis, or real-time systems is desirable. Experience with parallel computing and optimization techniques for handling large datasets