Research Associate, Control Systems job with NATIONAL UNIVERSITY OF SINGAPORE

job description

Your daily schedule will include frequent interactions with members of a multidisciplinary team.

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

The scope of the job

The research area for this position is in the development of control systems for an autonomous underwater vehicle operating in SS3 – SS4 swell conditions and currents up to 4 knots for stability in offshore conditions. We will explore various models (including heuristic, dynamic, and machine learning-based) for control system performance with adaptability to sinusoidal wave conditions as well as current-induced turbulence around underwater structures. In addition, the ability to maintain stability in the event of thruster failure will also be developed. Research will be developed around the Technology Center for Offshore Marine Singapore’s (TCOMS) Digital Twin Ocean Basin Model which will model the hydrodynamics of currents and waves around offshore structures.

The role will involve the following field of activity:

  • Research and implement control strategies for AUV control maneuvers
  • 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 control behavior
  • Integration of the control system with the robotics stack with the software architecture
  • Testing and debugging control algorithms in software in loop simulation

Qualifications

  • MSc in Computer Engineering/Mechatronics/Mechanical Engineering (Robotic Equivalent)
  • Research or industry experience writing code for complex robotic systems
  • Experience with complex control systems and AI
  • Experience with robotic operating system framework
  • Proficiency in Python and C++
  • Linux proficiency
  • Experience with reinforcement learning is a plus

More information

Location: Kent Ridge Campus

Organization: Engineering

Department: Mechanical Engineering

Eligible Employee Referral: No

Job Application ID: 6863