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experience with computer modelling, (e.g. agent-based modelling), as well as good grasp of machine learning, forecasting techniques, scenario planning, optimisation, Python and GIS. Good knowledge of English
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ideas into production-quality code. Processes are lightweight and agile: short goals, rapid iterations, direct contact with instructors and other stakeholders. All of our code is open and freely available
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100%, Zurich, fixed-term The Laboratory of Energy Science and Engineering (LESE) headed by Prof. Müller (ETH Zürich, Department of Mechanical and Process Engineering) is looking for a highly
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morphogenetic processes. Job description We are looking for a highly motivated postdoctoral researcher to: Develop and integrate numerical solvers for reaction-diffusion systems Extend the existing C++ codebase
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processes. Job description We are seeking a highly motivated PhD student to further develop this framework by: Implementing numerical solvers for reaction-diffusion systems Extending the biophysical
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and arrest, building structures with topologically interlocked materials, revealing the processes governing the structural build-up of cement in additive manufacturing, determining the nano- and micro
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controlling atmospheric composition, the detailed processes controlling this exchange are not well understood and highly parameterized in models. Long-term eddy flux observations, which are very limited world
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afterwards. You will work closely with our research team to implement a new version of our RAG-based chatbot. Profile The ideal candidate will be a computer or data science student, or a student with extensive
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standards and needs. Manage the operational process of onboarding new startups to the ETH AI Center – from first contact through to official affiliation.Develop a strong local network to grow the affiliated
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date: 1. July 2025. Your responsibilities: All aspects of flow cytometry sorter and analyzer operation, including quality control, maintenance and troubleshooting on a wide range of flow cytometry