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Efficient and Reliable Numerical Solution of Dynamic Optimization School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Yuanbo Nie Application Deadline: Applications
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optimization of technical processes and products. We present the exciting range of applications of our collaborative software development MESHFREE: https://www.meshfree.eu/ Currently, our team is working
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about shape optimization and the new opportunities offered by numerical design in turbomachinery. Prior experience in CFD and/or CFD code development (Python, C++, Fortran) would be a significant
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simulation and optimization of PDE-based problems involving uncertainties or stochastic components. We are looking for an internationally recognized individual who is a leader in the field of Numerical
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promising technology for producing large and complex metal component. Although its potential has been widely demonstrated, significant challenges remain in optimizing the process to ensure the quality
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called Tiramisu [1]. Unlike existing frameworks, Tiramisu can perform advanced code optimizations that are hard to apply otherwise. Because of this, Tiramisu can generate fast code that outperforms highly
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. Propose, develop, and test enhancements (e.g., shock-capturing strategies or improved numerical schemes). 3. Idealized supersonic flow simulations: Using the optimized code, conduct idealized simulations
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Research Associate to
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areas will be considered when selecting candidates: Machine Learning, Neural Networks, Numerical solutions of Partial Differential Equations and Stochastic Differential Equations, Numerical Optimization
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will be extended to three-dimensional roughness configurations, requiring the development of dedicated numerical tools optimized for high-performance computing environments. Results will be