Research Fellow (Digital Twin)

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 highly motivated and skilled Research Fellow to join the Robotics Research Centre (RRC) at NTU. The position will involve the human-in-the-loop robotic simulation leveraging digital twin technologies and robotics foundation models to enhance the intelligence of assistive robots.

Key Responsibilities:

• Develop human-in-the-loop robotic simulator to provide in-silico trials for assistive robots.

• Build virtual human models based on ability data and machine learning.

• Optimize robot parameters to cater for the personalised assistance for ADL tasks.

• Drive translational research in collaboration with clinical and industrial partners.

• Provide mentorship to research students and junior researchers.

Job Requirements:

• PhD degree in Computer Science, Robotics, Biomechanics or related engineering discipline.

• Strong experiences in one or more fields of data-driven robotics, reinforcement learning, embodied AI, virtual human modeling and simulation.

• Proficient in C/C++, Python and physics simulation engine (e.g. MuJoCo).

• Good analytic and communication skills, fast learner, ability to multi-task efficiently.

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