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-, landscape-, and regional scales. Assess and address scaling-related distortions in forest dynamics forecasts and ecosystem service evaluations; develop methods to reduce these effects. Develop measurable
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to enhance stability, reduce variability, and enable data-driven optimization and maintenance strategies. Job description Your Tasks Develop and implement AI methods for in-process monitoring of surface
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high-pressure and high temperature experimental (laser-heated and externally-heated diamond anvil cell, large volume press, and piston-cylinder apparatus) methods, eager to contribute to cutting-edge
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100%, Zurich, fixed-term The CMR group at the Institute for Biomedical Engineering develops Magnetic Resonance (MR) technology and methods to assess the cardiovascular system. We devise the next
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features. Additionally, as part of the SDSC, you will be part of a dynamic team working on applying machine learning methods to various fields, from environmental to political sciences, which will allow you
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dynamics using a broad range of mathematical, computational, and experimental approaches to study the population dynamics and evolution of infectious pathogens on both the within and between-host level (1 ,2
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maintenance, development and implementation of new analytical methods and new data analysis strategies are part of the responsibilities, as is the participation in the training and teaching of graduate students
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100%, Zurich, fixed-term The Distributed Computing (DISCO) Group is a research group at ETH Zurich, led by Prof. Dr. Roger Wattenhofer . We are interested in a variety of research topics on new and
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develop and run the weather and climate model ICON. We are seeking a High Performance Computing (HPC) software engineer to further develop and optimize the ICON model (80-100%). Project background In order
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comprises a multi-disciplinary team of data and computer scientists and experts in several domains, with offices in Zürich, Lausanne, and Villigen. MeteoSwiss, the Federal office for Meteorology and