Research Fellow – Multi-Agent RL for Autonomous Drone Swarm

About the role

The School of Mechanical & Aerospace Engineering at NTU seeks a Research Fellow to advance learning‑based algorithms for cooperative target tracking with autonomous drone swarms. The role focuses on multi‑agent reinforcement learning, decentralized task allocation, and robust coordination in complex, urban environments.

Key responsibilities

• Design and implement learning frameworks for multi‑agent robotic systems operating in cluttered settings.
• Formulate decision‑making problems, including state/action representation, reward design, and decentralized policy learning.
• Develop reinforcement‑learning and multi‑agent RL algorithms for target‑following under uncertainty and partial observability.
• Create perception‑aware decision methods that adapt to dynamic targets and environments.
• Integrate perception, decision‑making, and control modules within a simulation‑based validation platform.
• Conduct simulation experiments to assess performance, robustness, scalability, and generalisation.
• Collaborate with PhD students, research engineers, and external partners on system integration, testing, and demonstrations.
• Prepare technical reports, research papers, presentations, and project deliverables.

Required profile

• PhD in Robotics, Aerospace Engineering, Mechanical Engineering, Electrical & Electronic Engineering, Computer Science, Artificial Intelligence, or a closely related field.
• Strong research background in multi‑agent reinforcement learning, multi‑robot systems, or autonomous systems.

Required skills

• Multi‑agent reinforcement learning
• Decentralised policy learning
• Simulation‑based validation
• Perception‑aware decision making