Research Engineer (Applied Control & Autonomy - Drone Swarms & Security) - WLB1

Job Description

Research Engineer (Applied Control & Autonomy - Drone Swarms & Security) - WLB1

Posting Start Date: 05/03/2026

Schemes of Service: Research

Division: Engineering

Employment Type: Fixed Term

Job Title: Research Engineer – Applied Control & Autonomy (Drone Swarms & Security)

Location: SIT Punggol Campus

Job Type: Contract

Experience Level: 3+ years relevant experience (preferred)

About Us

Autonomous Systems Advanced Intelligence Laboratory (ASAIL) is at the forefront of developing next-generation unmanned aerial capabilities for the public safety sector. We are bridging the gap between commercial drone hardware and the demanding requirements of law enforcement and security operations. Our mission is to enhance the safety and effectiveness of personnel through intelligent, resilient, and autonomous aerial systems.

We are currently seeking a highly motivated Research Engineer to lead the applied research and development of advanced control augmentation techniques for Commercial Off-The-Shelf (COTS) drones. This role focuses on pushing the limits of COTS hardware by integrating sophisticated software and edge computing solutions.

The Role

As our Research Engineer, you will be responsible for the end-to-end development of augmentation software, from theoretical design and simulation to real-world proof-of-concept demonstrations. You will work on a portfolio of critical enhancements, including advanced navigation algorithms, swarm intelligence, cyber security hardening, and payload-specific control systems.

Key Responsibilities

• Control Augmentation Development: Design, implement, and tune advanced control augmentation techniques (e.g., model predictive control, adaptive control) to enhance the stability and agility of COTS drones under dynamic conditions.
• Swarm Intelligence: Develop and test decentralized swarm algorithms for coordinated area search, target tracking, and collaborative task allocation without reliance on constant ground control intervention.
• Cyber Security Enhancement: Research and implement mitigation strategies against common attack vectors on COTS platforms, including GPS spoofing, communication jamming, and protocol vulnerabilities. Develop hardened communication layers between the drone, edge device, and ground station.
• Payload-Specific Control: Integrate and tune control systems for mission-specific payloads (e.g., gimbaled cameras, spotlights, delivery mechanisms) to ensure stable operation and precise control during flight.
• Edge Computing Implementation: Architect and deploy machine learning and computer vision models directly onto onboard edge devices (e.g., NVIDIA Jetson) for real-time object detection, tracking, and autonomous decision-making.
• Proof-of-Concept Demonstration: Lead the integration of software onto physical drone platforms, conduct rigorous flight testing, and execute live demonstrations to validate performance against operational requirements.
• Documentation & Dissemination: Document research findings, software architectures, and test results. Prepare reports and presentations for internal and external stakeholders.
  
  

Required Qualifications & Expertise

• Education: Honor’s degree (Master’s and Ph.D. preferred) in Robotics, Computer Science, Electrical Engineering, Aerospace Engineering, or a related field.
• Control Theory: Strong theoretical and practical background in control systems, including PID, LQR, MPC, or adaptive control.
• Robotics Software: Extensive experience with the Robot Operating System (ROS/ROS 2).
• Programming: High proficiency in C++ and Python for real-time robotic applications.
• Simulation: Experience with realistic simulation environments such as Gazebo, AirSim, or Unreal Engine.
• Edge Computing: Proven experience deploying algorithms on resource-constrained edge devices for real-time inference and control.
• Drone Platforms: Hands-on experience with commercial autopilots (PX4, ArduPilot) and integrating software with COTS frames (DJI, Holybro, etc.) via companion computers.
• Swarm Robotics: Familiarity with consensus algorithms, formation control, and communication protocols for multi-agent systems.
• Security: Understanding of wireless communication protocols (Wi-Fi, 4G/5G, MAVLink) and common cybersecurity vulnerabilities in drone systems.
  
  

Preferred Skills (Bonus)

• Experience in law enforcement, defense, or public safety technology projects.
• Knowledge of computer vision techniques for object detection and tracking (YOLO, OpenCV).
• Experience with RF signal analysis or spectrum monitoring.