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numerical solvers for 2D and 3D phase field models Develop HPC-ready simulation pipelines for large-scale rupture and fracture-fluid systems Optimize performance for modern architectures including GPUs and
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Development of new multidomain simulation platform for electric motor drives Development of new fabrication methods for electric motor drives Experimental testing for motor system Job Requirements: PhD degree
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ecological theories to advance our understanding of ecosystem functions and their response to climate change. Job Description The ideal candidate is expected to be highly creative, have strong numerical and
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(CFD) methods. The role focuses on transitioning legacy CFD solvers to modern, Python-based AI frameworks (e.g., PyTorch, JAX), targeting high-efficiency, scalable simulations of water-air systems with
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strong numerical and critical thinking skills, and the ability to work in a diverse environment. This position is funded by Southeast Asia Innovation Alliance for a Global Model of Future Agri-food Systems
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The School of Mechanical & Aerospace Engineering (MAE) invites applications for the position of Research Fellow to undertake a project to develop efficient theoretical, numerical and experimental
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Responsibilities: Development of stochastic and analytical methods for nonlinear partial differential equations Implementation of relevant numerical experiments using deep learning algorithms Job Requirements: PhD
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published many high impact papers in top scientific journals such as Science, PNAS, Phys. Rev. Lett., etc. Our approach is highly interdisciplinary, using emerging state-of-the-art methods from mathematics