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an expanded coherent and exascale-ready software stack featuring breakthrough research advances that meets the needs of complex parallel applications and the requirements of heterogeneous exascale architectures
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(or to be obtained the year of the application) or other degree, depending on the scholarship applied for Being able to demonstrate excellent study results (great distinction or multiple distinction) and/or
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of multiple medicines across cellular mechanisms in parallel, ensuring accelerated assessment of existing and new therapies. Improving our understanding of the cellular basis of disease will help bridge the gap
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-scale scientific data. Publishing research in leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources
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journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation
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interdisciplinary team. Please keep your eyes open for related positions advertised in parallel to this one. If you see yourself to be qualified for more than one of them, please re-submit your application for each
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parallel, the role includes project oversight responsibilities, supporting effective coordination of consortium activities, organisation of meetings, and management of industrial site visits required
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philosophy to improve the modelling and governance of biodiversity under uncertainty. The project develops process-explicit, hierarchical models that capture key ecological dynamics, integrate diverse and
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depends on the ability to support local people and communities everywhere. By working in and across multiple scientific areas, CALS can address challenges and opportunities of the greatest relevance, here
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environment is a fundamental human right. We believe that ensuring a prosperous global future depends on the ability to support local people and communities everywhere. By working in and across multiple