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Job Description
A Research Fellow position is open in the research group of Prof. Shuzhi Sam Ge at the Department of Electrical and Computer Engineering, National University of Singapore (NUS).
Job Description
This project will combine the strengths of machine learning and control coupled physics-AI models can help to provide greater visibility and accuracy on carbon emissions estimation.
The successful candidate is required to:
- Develop physics models that capture the dynamics of ship engines and vessels, including the interactions between the hull, propeller, and engine;
- Research on the physical-informed neural network (PINN)-based method for the automated surface vessel prediction model that integrates deep learning neural networks into the nonlinear model predictive framework;
- Reduces carbon emissions and enhances the interpretability and adaptability of environmental sustainability measures across various maritime conditions;
- To advance the knowledge, to publish in leading journals, conferences, or patents;
- To prepare and meet the project deliveries and milestones.
Qualifications
Qualifications
- A PhD in Engineering, Physics etc, with specialization related to machine learning, control science, computer engineering or related field;
- Prior experience in control theory, hardware experience is advantageous;
- Strong programming skills in one of the programming languages: Python, C/C++, Matlab, etc;
- Have prior project related experience and be able to work independently;
- Strong organizational, writing and interpersonal communications.
- Open to Fixed Term Contract.
