Research Fellow, Department of Electrical and Computer Engineering

Tuesday, 16 March 2021
End of advertisement period
Friday, 16 April 2021
Contract Type
Fixed Term
Full Time

Job Description

A Research Fellow position is open in the research group of Assistant Professor Zhao Lin, at the Department of Electrical and Computer Engineering, National University of Singapore (NUS).   

The Research Fellow will work closely with the Principal Investigator (PI) on one or more research projects. One focus of these research projects is on the design and analysis of reinforcement learning algorithms, to improve the learning efficiencies and to provide theoretical performance guarantees, such as stability, convergence rate, optimality, etc. Another focus is to develop AI-assisted planning and control algorithms to enable more intelligent and robust autonomous operations and multi-agent collaborations. The design will be demonstrated through UAVs (unmanned aerial vehicles).

The candidates will be responsible for conducting theoretical research on control, learning, and game theory, designing new control and learning algorithms, and algorithm verification through simulation and real experiments.


  • Possess a Ph.D. Degree in either Electrical Engineering or strictly related (e.g., Mathematics, Computer, Communication, Mechanical, or Information Engineering).  
  • Have substantial research experiences in control, reinforcement learning, game theory, autonomous driving, and/or UAVs.  
  • Have expertise in control theory, reinforcement learning theory, and game theory. 
  • Possess a strong academic record proved through coursework (especially math-intensive courses) and projects during his/her undergraduate and doctoral studies.
  • Proficient in C++ or Python. Familiar with machine-learning tools and packages.
  • Have well-established analytical and problem-solving skills, as documented by publications that are relevant to the field of reinforcement learning and control for robotics applications.
  • Possess a solid mathematical background (such as in calculus, linear algebra, ODE/PDE, real analysis, measure theory, probability theory, stochastic process, optimization, etc).  Strong publication record in leading journals and conferences are highly valued. Practical hands-on experience of applying reinforcement learning to real robotics applications (e.g., autonomous driving, unmanned aerial vehicles) will be a big plus.
  • Excellent communication skills as he/she is required to publish and to present results at conferences and journals independently.
  • Activity performed in world-class research environments is highly valued.
  • Open to fixed-term contract.

Similar jobs

Similar jobs