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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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capabilities of the existing C++ codebase Applying the framework to morphogenetic problems using real imaging data Conducting large-scale simulations on ETH's HPC infrastructure Performing model calibration
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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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research, or a related field is a must • Proficiency in bioinformatics or clear motivation and prior exposure; HPC and metagenomics pipeline experience preferred • Experience with next-generation sequencing
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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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bioinformatics-related images for computational pipelines. Evaluate and procure compute resources for High-Performance Computing (HPC) platforms, managing access. Write automation scripts (e.g., Python