Research Fellow (Coastal modelling with AI)
Job Description
The Research Fellow (RF) will conduct research in the field of coastal dynamics, with a focus on the development and application of machine-learning-enhanced coastal models. The project aims to advance nearshore hydrodynamic modelling by integrating data-driven and physics-based approaches for simulating wave propagation, wave transformation, and wave–current interaction from deep water to shallow coastal environments.
The successful candidate will work on developing and improving depth-integrated, phase-resolving coastal models, with machine learning techniques incorporated to enhance model accuracy, efficiency, parameterisation, uncertainty quantification, and/or surrogate modelling. The research may involve the use of observational, experimental, or high-fidelity numerical data to train, validate, and improve model performance.
The developed model will be applied to coastal engineering problems, including wave transformation, nearshore circulation, and extreme coastal processes. Depending on the project needs, the model may also be coupled with high-resolution CFD models to enable multi-scale coastal process modelling.
Job Requirements
- Possess a PHD in related field such as coastal and ocean engineering.
- Preferably with experience and knowledge in numerical modelling, hydrodynamics, wave theories, and artificial intelligence.
- Strong written and spoken communications.
- Strong quantitative skills.
- Having pior good publication record is advantageous.
- Open to fixed-term contract.
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