Research Fellow – AI & Machine Learning for Fluid-Structure Interaction

About the role

The School of Mechanical & Aerospace Engineering at NTU seeks a Research Fellow (postdoctoral level) to develop efficient AI and Machine Learning techniques for fluid‑structure interaction problems. The role combines theoretical work, numerical simulation, and experimental validation within a multidisciplinary research environment.

Key responsibilities

• Develop AI‑driven and physics‑enabled data‑driven methodologies for fluid and structural analysis.
• Conduct numerical simulations and experimental investigations of fluid‑structure interaction.
• Innovate and explore technologies for potential industrial applications.
• Publish high‑quality research articles to disseminate findings.
• Manage project administration tasks and liaise with collaborators.
• Provide regular progress updates and reports.

Required profile

• PhD in Computer Science, Mechanical, Electrical, Aerospace Engineering, Physics or a related discipline.
• Strong theoretical and numerical skillsets.
• Experience applying AI and Machine Learning to engineering problems.
• Proven track record of scientific publications.
• Good interpersonal skills, teamwork awareness, and strong research responsibility.

Required skills

• Artificial Intelligence
• Machine Learning
• Numerical simulation