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Employer
- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
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- UNIVERSITY OF NOTTINGHAM NINGBO CHINA
- Harbin Engineering University
- Beijing Normal-Hong Kong Baptist University (BNBU)
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Field
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fundamental problems arising in mathematical fluid dynamics and turbulence, including regularity properties of solutions to the Navier-Stokes, Euler, and related equations, dissipation anomaly, Onsager’s
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fluid mechanics, computational geometry, meshing, computational graphics, computational vision, or scientific machine learning in general. Successful candidates will join a community of researchers in
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. Possible research topics include: Scientific machine learning Numerical partial differential equations (PDEs) Computational fluid dynamics Neural operators High-performance computing Data-driven
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, Computational Fluid Dynamics, Oceanic and Atmospheric Simulations are encouraged to apply. Responsibilities for these positions include mathematical research, undergraduate and graduate teaching (1+1), and
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Equations, Optimization, Stochastic Differential Equations, Stochastic Partial Differential Equations, Mathematical Physics, Fluid Dynamics, Mathematical Biology, Mathematical Epidemiology are encouraged
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for modelling complex international scenarios, allowing policymakers and scholars to anticipate the consequences of strategic decisions, trade agreements, or environmental regulations. Geospatial
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Quantum Computation & Quantum Information, Cold Atoms & Many-Body Theory, Statistical Physics & Complex Systems, and other related areas. Applicants must possess a PhD in physics or a related field. The
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. Furthermore, AI-driven simulations offer a transformative tool for modelling complex international scenarios, allowing policymakers and scholars to anticipate the consequences of strategic decisions, trade
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, candidates must demonstrate a high level of English proficiency, including the ability to communicate complex ideas clearly and effectively in teaching, research, supervision and academic leadership contexts
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, multiphysics systems, complex physical processes, and data-driven scientific simulation. The successful candidate is expected to play a key role in developing physics-informed artificial intelligence methods