Research Fellow (Drone Swarm in Cluttered Environments)
NATIONAL UNIVERSITY OF SINGAPORE
Singapore, Singapore
Not specified
Python programming with pytorch
Deep reinforcement learning expertise
Simulation environment development (isaac lab/ros gazebo)
The National University of Singapore is seeking a Research Fellow to develop multi-agent reinforcement learning techniques for drone swarms operating in cluttered urban environments. The role requires strong programming skills, experience with simulations, and a background in deep learning for aerial robotics
Job Summary
This role focuses on developing deep multi-agent reinforcement learning approaches for teams of drones to search targets in low-rise urban environments.
The candidate will investigate both conventional pipelines and recent AI-based methods to design robust swarm planning strategies under real-world constraints.
Responsibilities include developing simulation environments for training AI policies and deploying controllers on hardware equipped with LiDAR and cameras.
Matching Summary
Match Score: 85
The National University of Singapore is seeking a Research Fellow to develop multi-agent reinforcement learning techniques for drone swarms operating in cluttered urban environments. The role requires strong programming skills, experience with simulations, and a background in deep learning for aerial robotics.
Skills & Requirements
Must-have
Python programming with PyTorch
Deep reinforcement learning expertise
Simulation environment development (Isaac Lab/ROS Gazebo)
LiDAR and camera sensor integration
Motion planning and mapping algorithms
Nice-to-have
Experience deploying AI on aerial robots
Semantic perception implementation skills
Publishing research papers
Supervising undergraduate or master's students
Transformer architecture knowledge
Key Requirements
Excellent coding skills in Python
Experience with distributed deep reinforcement learning