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Field
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understand infant cognition, develop neuroimaging methods to better detect disrupted function following neonatal brain injury, and identify new more energy efficient learning algorithms that could reduce the
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understand infant cognition, develop neuroimaging methods to better detect disrupted function following neonatal brain injury, and identify new more energy efficient learning algorithms that could reduce the
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 22 hours ago
Qualifications: Expertise in the development of seismic processing algorithms, high-performance computing, and/or large-scale inverse problems; Experience in developing open-source software and a track
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-Newtonian fluid dynamics, direct numerical simulations and machine learning algorithms, contributing to the development of new ideas, approaches, concepts or techniques. The role holder will contribute to
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downstream statistical inference. · Developing and implementing computationally intensive algorithms using high-performance computing (HPC) clusters. · Managing and analyzing multiple large
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quantum chemical methods and machine learning; developing quantum algorithms for computational chemistry on quantum computers; and applying existing and new computational methods to study multiscale
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, or a related field (e.g. statistics, computer science, or quantitative biology). Experience in the application and development of computational methods/tools or machine learning algorithms. Good
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, multiple machine‑learning algorithms, MOFA and multi‑omics pathway analysis. · Strong background in experimental design, quantitative data analysis, and scientific writing, evidenced by first-author
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the energy transition for citizens, industrial areas and energy access in developing countries, by e.g., developing novel power electronics, coordination algorithms and governance structures. For this
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successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high-dimensional data. Develop modular methods that incorporate