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numerical methods, high-performance computing (HPC), or large-scale data analysis. Experience in applying AI/ML techniques to hydrological and Earth sciences. Proficiency in scientific programming
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Natural Science and the College of Engineering. CMSE centers around computational approaches, encompassing algorithm development, high-performance computing, scientific modeling, and data science
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scientific computing, control theory, data science, data driven methods, discrete mathematics, discretization methods, graph algorithms, high-performance computing, integral equations and nonlocal models
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scientific conferences, and communicate results to stakeholders and breeding teams. • Leverage existing computing infrastructure, including the Arkansas High Performance Computing Center (AHPCC, https
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publicly available datasets to interpret results in a robust biological context Ensure reproducibility, data management, and documentation of computational workflows in high-performance computing
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of mission-critical systems. The position plays a key leadership role in: Advancing digital transformation initiatives Supporting data-intensive research and high-performance computing needs Enabling
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
safeguard Australia’s future. At the heart of ACCESS is a community of Research Software Engineers with a range of skills including high-performance computing and data (HPCD), climate and Earth system
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
safeguard Australia’s future. At the heart of ACCESS is a community of Research Software Engineers with a range of skills including high-performance computing and data (HPCD), climate and Earth system model
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, engineering and the life sciences. The Interpretable Machine Learning Lab has dedicated access to high-performance CPU and GPU computing resources provided by Duke University’s Research Computing unit
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Qualifications: Basic understanding of the DOE national laboratory system and preferably its variety of user facilities, including its high-performance computing user facilities. Working knowledge of why