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.

The School of Mechanical and Aerospace Engineering (MAE) is seeking to hire a Research Fellow to lead the development of next-generation computational tools for simulating particle-laden two-phase flows by integrating advanced Artificial Intelligence (AI) techniques with traditional computational fluid dynamics (CFD) methods. The role focuses on transitioning legacy CFD solvers to modern, Python-based AI frameworks (e.g., PyTorch, JAX), targeting high-efficiency, scalable simulations of water-air systems with solid particle transport. The successful candidate will contribute to the creation of an AI-optimized platform capable of achieving up to 50× speedups in simulation performance, enabling real-time, energy-efficient modelling for complex multiscale flow phenomena relevant to coastal engineering, turbomachinery, and additive manufacturing. This position is central to advancing AI-augmented fluid dynamics and delivering an open, sustainable simulation tool for the research and engineering community.

Key Responsibilities:

• Development of AI-augmented CFD frameworks
• Simulation of particle-laden two-phase flows
• Valid the numerical model with experimental or existing numerical work
• Publish high-impact research
• Engage in interdisciplinary collaboration

Job Requirements:

Education qualifications

• PhD in Mechanical Engineering, Computational Science, Applied Mathematics, or a related field.

Soft skills

• Critical thinking and problem-solving,
• Collaboration and teamwork,
• Good communication,
• Time management and self-motivation

Hard skills

• Strong foundation in CFD,
• Programming proficiency such as Python, AI/ML techniques,
• Experience with parallel computing on CPU/GPU cluster,
• use of CUDA, MPI is a plus.

Experience

• Experience with open-source CFD frameworks (e.g., OpenFOAM, Basilisk, or similar) is advantageous,
• Demonstrated track record of peer-reviewed publications in relevant fields.

Competencies

• Capable of proposing and implementing novel computational strategies that go beyond traditional CFD paradigms,
• Enthusiastic about exploring new AI paradigms and applying them to engineering challenges.

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