Research Fellow (Computer Science/ Mechanical/ Electrical/ Aerospace Engineering/Physics)

The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE prides itself in its excellent research capabilities in areas including advanced manufacturing, aerospace, biomedical, energy, industrial engineering, maritime engineering, robotics, etc. The school is equipped with state-of-the-art research infrastructure, housing a comprehensive range of cluster laboratories, test bedding facilities, research centres/institutes and corporate laboratories. Cutting-edge research in MAE addresses the immediate needs of our industries and supports the nation’s long-term development strategies. In the new era of industrial 4.0 and sustainable living, MAE is rigorous in developing new competencies to support the growth and competitiveness of our engineering sector in the global landscape. MAE has grown to be leader in Engineering Research, ranking amongst the top engineering schools in the world.

For more details, please view https://www.ntu.edu.sg/mae/research.

We are looking to hire a research fellow (postdoc) to undertake a project to develop efficient AI and Machine Learning techniques for investigation of fluid-structure interaction problems.

Key Responsibilities:

• Undertake theoretical development of AI and physics-enabled data driven methodologies for fluids and structure

• Undertake and numerical simulations and experiments

• Innovate and seek technologies for potential applications

• Publish quality research articles to disseminate study findings

• Undertake project administrations and liaison

• Provide regular updates and reports

Job Requirements:

• Possess a recognized PhD degree in Computer Science / Mechanical / Electrical / Aerospace engineering or Physics or related disciplines.

• Good theoretical and numerical skillsets

• Experience in AI and ML in Engineering applications

• Good track record in scientific publication

• Good interpersonal skills. Excellent teamwork awareness

• Strong responsibility for research / work

We regret to inform that only shortlisted candidates will be notified.