Research Fellow (physics-informed Neural Networks (pinns))

NTU (Nanyang Technological University)

Singapore
Strong background in machine learning
Experience with pinns
Proficiency in python and/or c/c++
The School of Mechanical & Aerospace Engineering is a dynamic international research community

Job Summary

  • The School of Mechanical & Aerospace Engineering is a dynamic international research community.
  • The role focuses on the development of PINNs and their experimental validation on quadruped robots.
  • MAE is rigorous in developing new competencies to support the growth of the engineering sector.

Matching Summary

The School of Mechanical & Aerospace Engineering is a dynamic international research community.

Skills & Requirements

Must-have

  • Strong background in machine learning
  • Experience with PINNs
  • Proficiency in Python and/or C/C++

Nice-to-have

  • Curious and ambitious mindset
  • Effective time management skills
  • Ability to work independently and collaboratively

Key Requirements

  • PhD in Robotics or related field
  • Excellent verbal and written communication skills
  • Strong work ethic

Work Rights

Not specified

Tailored Resume

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