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- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
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Field
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science with numerical modelling to understand and improve nitrogen fixation pathways, alongside the use of analytical chemistry methods to quantify nitrogen-containing products and assess system
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Scholar in physical oceanography focused on numerical ocean modeling, ocean data assimilation, and computational methods for understanding and predicting regional and coastal ocean circulation. This is
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at King’s on quantum algorithms and numerical methods for many-body dynamics beyond the reach of standard classical simulation. About the role We have a high preference for a candidates who is willing
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working on developing experimental and numerical methods for wind turbine aerodynamics. The particular areas of responsibilities include: High and low-fidelity modelling of wind turbine airfoil and
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> on research projects related to kinetic equation and its related multiscale model reduction, numerical method, and data-driven/machine-learning approaches, including: • Numerical simulation of kinetic
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, numerical method, and data-driven/machine-learning approaches, including: · Numerical simulation of kinetic equations: fast algorithms with stability/convergence analysis; · Data-driven and machine
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, or a related field. Experience with numerical discretization methods for partial differential equations. Experience in computational modeling of geomechanical systems. Knowledge of continuum
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experimental methods where appropriate. Process, interpret and manage research data, and contribute to integrating laboratory results with seismological observations and numerical modelling. Plan and manage
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of acoustic wave physics and numerical simulation methods. Experience with finite-element methods tools such as COMSOL is highly desirable. 4, Proficiency in scientific programming and data analysis
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 5 hours ago
) for a collaborative project with a starting date of April 1, 2020. The candidate will be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and