191 parallel-computing-numerical-methods-"https:" positions at ETH Zurich in Switzerland
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of methods to program material stiffness in-situ with light. Goals: high stiffness contrast (rigid-soft), fast transition (<1s), and small form factor (< mm scale) Characterization and developing theoretical
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a major role in the advent of the Information Age - One high bandwidth fiber optic cable can replace thousands of electrical links to transmit the same amount of information. As a parallel to the
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of the Information Age - One high bandwidth fiber optic cable can replace thousands of electrical links to transmit the same amount of information. As a parallel to the thriving fields of soft devices and robots
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100%, Zurich, fixed-term The Advanced Manufacturing Lab (am|z) at the Department of Mechanical & Process Engineering (D-MAVT) at ETH Zurich develops advanced manufacturing methods and systems
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findings into technical improvements (e.g., new embedding methods, agent architectures, prompting strategies) Publishing research results in leading venues in artificial intelligence and computational social
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. The project provides a unique opportunity to study judicial decision-making in a real-world institutional setting, combining legal analysis with experimental and empirical methods. Job description The doctoral
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innovative methods to leverage machine learning for numerical weather forecasting and climate modeling. Project background We are looking for a motivated Machine Learning Scientist to join the development team
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innovative methods to leverage machine learning for numerical weather forecasting and climate modeling. We are looking for a motivated Machine Learning Scientist to join the WeatherGenerator project. Like
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expertise to enable real-time sequence analysis and deliver clinically actionable results within hours. Job description You will develop and implement novel computational methods for the analysis of long-read
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engineering Strong background in computational science, applied mathematics, or computational biology Ideally, familiarity with numerical methods for PDEs (e.g., finite difference, finite element) HPC