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 seeking a Research Associate to develop a high-fidelity Artificial Intelligence (AI) framework for modeling viral droplet dispersion (AI4ViDro). The framework will integrate airflow, droplet transport, and human mobility under diverse environmental conditions. The role will focus on modernizing legacy Computational Fluid Dynamics (CFD) solvers into Python-based AI frameworks (e.g., PyTorch, JAX) to enable high-efficiency, scalable simulations of aerosol transport systems. The developed model will incorporate human mobility and respiratory activities into the CFD solver to realistically represent social interactions and human behavior in various environments on the respiratory disease transmission.
Key Responsibilities:
Development of AI-augmented CFD frameworks
Simulation aerosol transmission and human mobility
Valid the numerical model with experimental or existing numerical work
Engage in interdisciplinary collaboration
Job Requirements:
Education qualifications
Master degree or higher 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,
Use of CUDA, MPI is a plus.
Experience
Experience with CFD simulation tools (e.g., OpenFOAM, Ansys Fluent, 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.
Hiring Institution: NTU