Research Fellow (Physics-Informed Neural Networks (PINNs)) Full-time

Research Fellow Position

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.

We are looking for a Research fellow to work on the development of Physics-informed neural networks (PINNs) on quadruped robots. The role will focus on the development of PINNS and their experimental validation on quadruped robots.

Key Responsibilities:

• Lead and contribute to experiments, simulations, or theoretical work aligned with the project's goals.
• Lead and co-author peer-reviewed journal articles, conference papers, or technical reports.
• Plan timelines, manage resources, and report progress to the Principal Investigator.
• Build your own research profile and prepare for the next career stage.

Job Requirements:

• A PhD degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, Applied Maths, Physics, or any related field
• Strong background in machine learning, PINNs and control theory
• Excellent verbal and written communication skills
• Proficiency in programming languages in Python and/or C/C++.
• A curious and ambitious mindset for research
• A strong work ethic, effective time management skills, and a capability to work independently and collaboratively

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

Hiring Institution: NTU