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Field
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interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific computing and machine learning. The research will emphasize both theoretical
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deep learning and scalable deployment Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches Design and run experiments using the latest
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candidate will design and develop digital twin algorithms for computational fluid dynamics, contributing to innovative solutions in healthcare software systems. This role involves collaboration with research
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to develop advanced algorithms, parallel computing capabilities, and software engineering of Green’s function based multiple-scattering code for computing the electronic structure and energetics
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the gap between cutting-edge ML research and practical implementation Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches Design and run
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(UESTC) located in Chengdu, China. We are looking for highly qualified and motivated candidates to participate in a research project to develop applications for near term quantum computing devices
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years of related experience. Experience using Python for algorithm development, data science, and/or machine learning. Experience using JavaScript for front-end web development and visual data analysis
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. Experience using Python for algorithm development, data science, and/or machine learning. Experience using JavaScript for front-end web development and visual data analysis. Familiar with the software
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(UNSW), Prof. Brendan McKay (ANU) and Prof. Ian Wanless (Monash). The project aims to develop new theoretical tools to address fundamental challenges about graphs and hypergraphs with given degrees
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and