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Python and Fortran Familiarity with climate data formats (e.g. NetCDF) and relevant tools (e.g. xarray, CDO) Proficiency with Linux/Bash and Git version control Experience with HPC/supercomputing
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foundation models (e.g., Google Earth AI, AlphaEarth, TerraTorch) on a cutting-edge HPC platform. The researcher will conduct publishable scientific research while building tools and pipelines that serve
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for reaction-diffusion systems Enhancing the biophysical capabilities of the C++ framework Applying the framework to morphogenetic questions using real imaging data Running large-scale simulations on ETH’s HPC
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processing large datasets or experience in high-performance computing (HPC) is an advantage Experience with weather and climate applications and weather ensemble forecasting is an advantage You are creative
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computing (HPC) is an advantage Experience with weather and climate applications is an advantage You are creative, solution-oriented and have excellent communication skills and the ability to work with
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), and workflow automation on HPC systems At least 3 years of interdisciplinary work experience (PhD not included) Strong communication skills for working across different scientific disciplines Beneficial
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data analysis and visualization Desired qualifications and skills: Prior experience with either severe thunderstorm dynamics or numerical modeling Familiarity in working with Linux on HPC clusters
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is to design, implement, and operate scalable inference services within a multi-tenant HPC infrastructure As a systems engineer, you will play a key role in the architecture deployment, operation, and
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, optimized for high-performance computing (HPC) environments Classifying ice crystal habits using Convolutional Neural Networks (CNNs) Providing intuitive graphical interfaces for user interaction and data
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is an advantage Familiarity with Linux-based computing environments; experience with high-performance computing (HPC) systems is an advantage Knowledge of reproducible research practices, including