Research Associate (Generative Design) - D22 Jurong, Jurong Island, Tuas, SG

Roles & Responsibilities

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 for a Research Associate to develop novel AI-based generative design methods for heat exchanger for energy saving purpose. The role will focus on geometric representation, multi-physics numerical simulations, machine learning and manufacturability constrained design optimization given metal additive manufacturing process. We expect the candidate to use data-efficient AI methods to deliver optimized designs that achieve superior thermal performance and satisfy the manufacturability requirements.

Key Responsibilities :

The Research Associate will work on a cross-disciplinary project at the intersection of fluid mechanics, numerical simulation, design optimization and machine learning. The key responsibilities of this position include :

• Perform numerical simulation to solve heat transfer problems
• Develop cost-efficient machine learning-based surrogate models
• Perform design optimization based on AI
• Incorporate manufacturability concerns
• Collaborate with internal and external stakeholder on energy systems
• Maintenance of lab or equipment or supplies that include procurement and liaison with suppliers
• Assist or produce high quality reports and documents that consolidate research findings

Job Requirements :

Required educational qualification, experience, skills and competencies for this position :

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

Tell employers what skills you have

Aerospace Engineering

Machine Learning

Data Analysis

MetaL

Heat Transfer

Additive Manufacturing

Industrial Engineering

Python

Publications

Simulations

Robotics

Manufacturing

Mechanical Engineering

C++