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- into a GPU-enabled and parallel code to run efficiently on state-of-the-art exascale hardware Designing implementations and reviewing community contributions of library features and new statistical
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plasma. The main methods used are computer simulations for studying dust dynamics and analysing in situ measurements by spacecraft that carry a dust detector on board. We collaborate with researchers in
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requirements. In parallel there’s been an expansion of AI-driven structural biology (e.g. Alphafold, prediction of disease mutations, prediction of molecular interactions). These projects require specialist
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evaluation, or a strong willingness to gain hands-on experience. Eagerness to learn HPC concepts, including parallel computing, distributed systems, and optimization. Analytical skills, problem-solving
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We are seeking an experienced and enthusiastic Cloud Engineer to be based at the Institute of Astronomy (www.ast.cam.ac.uk ) in collaboration with the Research Computing Services (www.hpc.cam.ac.uk
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) to organize, manage, and analyze genomic and genome-wide association study datasets using massively parallel computing infrastructure in the Minnesota Supercomputing Institute (MSI) and Google Cloud (50
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increasingly complex compute- and data-intensive problems in science and engineering on high-end parallel and distributed computing platforms. More information: https://sc.cs.univie.ac.at/ Your future tasks
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this, these simulations need to be massively parallelized. The objective of this thesis is to implement and evaluate different contingency parallelization approaches using our group's computational infrastructure
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volcanic environments. Development and flight testing will run in parallel with field campaigns at three key volcanic sites: Soufrière Hills Volcano (Montserrat), Fuego (Guatemala), and Lascar (Chile
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lead capacity and is considered a subject matter expert at this level. Using deep expertise in high-performance computing (HPC) systems, including resource managers, schedulers, and parallel file systems