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with additional biophysical features Apply the framework to morphogenetic problems based on imaging data Run large-scale simulations on ETH Zurich’s high-performance computing (HPC) infrastructure
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ETH’s high-performance computing (HPC) clusters A dynamic, interdisciplinary, and supportive research environment at the interface of biology, engineering, and computational science Flexibility
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Required experience: CH/EU/EFTA citizenship or a valid work permit for Switzerland A Master’s degree (ETH, university) in engineering, computer science, or a related field Strong academic performance meeting
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mutual learning. Access to high-performance computing. Terms of employment: The desired starting date is September 1st, 2025. We are looking for a postdoctoral researcher/senior scientist for an initial
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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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, continuous integration). Adapt software for parallel computing, optimization workflows, and high-performance computing environments. Contribute to software deployment, testing, and benchmarking across multiple
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– support daily platform operations in collaboration with the development team, perform database updates and data integrity checks Content workflows – implement and manage content across languages and
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80%-100%, Lugano, permanent The Swiss National Supercomputing Centre (CSCS) develops and operates cutting-edge, high-performance computing (HPC) systems as an essential service facility for science
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experience with genomic data analysis on a high-performance computing cluster, along with strong communication skills, is desirable. Profile Research interest in statistical genomics, computational biology
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. Experience with running numerical models is an advantage. Experience in working in a Linux/Unix high-performance computing environment is a plus. Good communication skills in English (written and spoken