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Field
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relativity, The analytical and numerical study of the potential breakdown of effective field theory methods outside black holes, The analytical and numerical modeling of the dynamics of (and gravitational
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 7 hours ago
of numerical simulations and digital twins. By using advanced machine learning methods, such as Physics-Informed Neural Networks (PINNs) and Variational Physics-Informed Neural Networks (vPINNs), the project
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mathematical analysis methods to ground proof numerical simulations Strong communication skills and ability to work across disciplinary boundaries. Desirable Experience with image-based modelling workflows (CT
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). Familiarity with asymptotic and multiscale mathematical analysis methods to ground proof numerical simulations Strong communication skills and ability to work across disciplinary boundaries. Desirable
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This post will advance the application of Machine Learning (ML) in weather forecasting and hydrological prediction. The Research Fellow will develop ML methods for postprocessing numerical ensemble weather
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Context Statement Position Overview A postdoctoral position is available in the Department of Physics at the University of Idaho. The primary focus of this position is advancing numerical relativity methods
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excellence of NTU and attracting interest of more industrial collaborators. Key Responsibilities: Develop a new and robust numerical model with lattice Boltzmann method to simulate flow and heat transfer with
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-driven methods. The role will focus on developing intelligent methods and operation-support tools for ATM applications, contributing to the advancement of research and innovation at Nanyang Technological
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conduct researches of transport phenomena and dynamics of chemical reaction using the approaches of active matter, nonequilibrium statistical physics, theory/mathematical calculation method of nonlinear
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Theory (DFT) calculations using established codes (e.g., VASP, FHI-aims). Demonstrated experience with traditional methods for modeling atomic site disorder, such as special quasi-random structures (SQS