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topical subject area. Participation in project meetings and conferences. Opportunities for limited-time research stays abroad. Access to state-of-the-art HPC and ML facilities via the de.NBI Cloud and the
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GPU-capable, parallelized simulation frameworks. Work closely with experts in HPC and power systems to enhance scalability and computational performance. Disseminate your findings through scientific
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-following inverters. Implementing and optimizing scalable algorithms for transient and stability analyses on HPC architectures (CPU, GPU, hybrid). Enhancing the numerical robustness and efficiency of existing
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fabrication facilities as well as high performance computing (HPC) facilities at QUT. PhD2: Pore-network modelling of reactive transport As a PhD student, you will develop efficient pore-network modelling
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, and highly collaborative environment. Other qualifications Applicants might have prior experience: Computing in HPC environments Programming in Rust Analyzing single-cell data, particularly scMetaG data
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, inclusive, interdisciplinary, and highly collaborative environment. Other qualifications Applicants might have prior experience: Computing in HPC environments Programming in Rust Analyzing single-cell data
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of computational power over the last decade has enabled scale-resolving simulations (SRS) of turbulent flows at an unprecedented resolution. In combination with high-performance computing (HPC), parallel
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with high-performance computing (HPC), parallel computational fluid dynamic simulations can currently resolve spatial and temporal scales of industrially-relevant turbulent flows within days/weeks
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and debugging, as well as software engineering best practices. You will have access to cutting-edge computational resources, including the latest Imperial College HPC clusters, and UK National
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partners. Training & environment You’ll gain deep skills in hypersonic flows, AI for PDEs, data assimilation, and reproducible HPC workflows (Python/C++/PyTorch/JAX). You’ll be supported with paper writing