Research Fellow, Control Systems

20 Dec 2021
End of advertisement period
19 Jan 2022
Contract Type
Full Time

Job Description

Your daily schedule will include frequent interactions with members of a multi-disciplinary team.

  • You are comfortable working at sea trials and pool tests, instead of a normal cubicle in office.
  • You build safe and scalable robotic systems with clean and documented code.

Job Scope

The research scope for this position is in control systems development for an Autonomous Underwater Vehicle operating in SS3 - SS4 swell conditions and currents of up to 4 knots for stability in offshore conditions. We will explore various models (including heuristic, dynamics and machine-learning based) for control system performance with adaptability to the sinusoidal swell conditions as well as turbulence induced by currents around subsea structures. Also, the ability to maintain stability in event of thruster failure will also be developed. The research will be developed around the digital twin model of the Technology Centre for Offshore Marine Singapore (TCOMS) ocean basin which will model the hydrodynamics of currents and waves around offshore structures.

The role will entail the following job scope:

  • Research and implement control strategies for the AUV control manoeuvres
  • Research and implement adaptive control systems capable of handling uncertainty in strong water currents and waves
  • Research and exploration of reinforcement learning type reward-prediction type control behaviour
  • Integration of control system with robotics stack with the software architecture
  • Test and debug of control algorithms in software in the loop simulation


  • PhD in Computer Engineering/ Mechatronics/Mechanical Engineering (Robotics Equivalent)
  • Research or industry experience writing code for complex robotic systems
  • Experience with complex control systems and AI
  • Experience with Robot Operating System framework
  • Proficient in Python and C++
  • Proficient in Linux
  • Experience with reinforcement learning is a bonus

More Information

Location: Kent Ridge Campus
Organization: Engineering
Department : Mechanical Engineering
Employee Referral Eligible: No
Job requisition ID : 6862

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