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Research Engineer (LWIR Perception & UAV State Estimation)

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National University of Singapore (NUS)

Kent Ridge Campus

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Research Engineer (LWIR Perception & UAV State Estimation)

Research Engineer

2026-06-29

Location

Kent Ridge Campus

National University of Singapore (NUS)

Type

Research Staff, Fixed Term

Start Date

2026-04-22

Required Qualifications

Bachelor’s in Computer/Electrical Engineering
Robot perception & state estimation experience
SLAM or sensor fusion
LWIR/thermal imaging preferred
C++/Python, ROS proficiency
UAV systems (PX4), Gazebo/AirSim
EKF/UKF, factor graph optimization
Sensor calibration & embedded deployment

Research Areas

LWIR Imaging
UAV State Estimation
Odometry & SLAM
Multi-sensor Fusion
Autonomous Navigation
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Research Engineer (LWIR Perception & UAV State Estimation)

University-Level Unit: College of Design and Engineering

Faculty/Department-Level Unit: Electrical and Computer Engineering

Employee Category: Research Staff

Location: Kent Ridge Campus

Posting Start Date: 22/04/2026

Job Description

A Research Engineer position is open at the Department of Electrical and Computer Engineering, National University of Singapore (NUS).

The Research Engineer will work closely with the Principal Investigator (PI) on the project on Long-Wave Infrared (LWIR) Imaging for Autonomous Navigation. The position focuses on developing robust perception, state estimation, and odometry algorithms using LWIR (thermal) imaging for UAVs operating under degraded visual conditions, such as low illumination, smoke, fog, and texture-sparse environments.

The Research Engineer will design and implement LWIR-based odometry and thermal-inertial state estimation frameworks, including multi-sensor fusion with IMU and other onboard sensors. The work will involve both model-based approaches (e.g., filtering and optimization-based estimation) and learning-enhanced methods for improving robustness and generalization across environments.

The candidate will also be responsible for system integration and real-world deployment on UAV platforms, including embedded implementation, sensor calibration, and experimental validation in both indoor and outdoor scenarios. The developed methods will be evaluated in realistic navigation tasks under challenging environmental conditions.

The initial appointment duration is 12 months, which can then be extended based on an evaluation at the end of the initial appointment.

The candidate should have a Bachelor’s degree from a reputable university, with expertise in robot perception, state estimation, or aerial robotics.

A successful candidate should have a strong mathematical background (e.g., linear algebra, optimization, probability, stochastic processes), along with demonstrated experience in state estimation, odometry, or SLAM systems, particularly in robotics applications.

Qualifications

  • Possess min a Bachelor’s degree in Computer Engineering/Science or related disciplines (e.g., Electrical Engineering, Mechanical Engineering, Mathematics).
  • Have research experience in robot perception, state estimation, SLAM, or sensor fusion.
  • Experience with thermal (LWIR) imaging, event cameras, or other non-RGB sensing modalities is highly preferred.
  • Familiar with visual-inertial odometry (VIO), thermal-inertial odometry, or multi-sensor fusion frameworks.
  • Knowledge of state estimation techniques, including EKF, UKF, factor graph optimization, or moving horizon estimation (MHE).
  • Experience with feature extraction or direct methods under low-texture or low-SNR conditions is a plus.
  • Proficient in C++ or Python; experience with ROS and real-time robotic systems.
  • Familiar with UAV systems (e.g., PX4), and simulation environments such as Gazebo or AirSim.
  • Experience in sensor calibration (intrinsic/extrinsic) and time synchronization is desirable.
  • Strong analytical and problem-solving skills, demonstrated through relevant publications or projects.
  • Ability to deploy algorithms on embedded platforms (e.g., NVIDIA Jetson) is a plus.
  • Excellent communication skills for publishing and presenting research outcomes.
  • Experience in world-class research environments is highly valued.
  • Open to Fixed Term contract

Apply now

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Frequently Asked Questions

🎓What are the key qualifications for this Research Engineer role at NUS?

Candidates need a Bachelor’s degree in Computer Engineering, Science, Electrical Engineering, or related fields. Essential experience includes robot perception, state estimation, SLAM, or sensor fusion. Preferred: LWIR thermal imaging, VIO, EKF/UKF, C++/Python, ROS, and UAV systems like PX4. Strong math skills in linear algebra and optimization required. Explore research jobs or research role tips for preparation.

🚁What responsibilities involve LWIR perception and UAV state estimation?

Develop LWIR-based odometry and thermal-inertial state estimation for UAVs in degraded conditions (low light, fog, smoke). Implement multi-sensor fusion with IMU, model-based (filtering/optimization) and learning methods. Handle system integration, embedded deployment on UAVs, sensor calibration, and real-world testing indoors/outdoors. Check similar research assistant jobs for insights.

📅What is the employment duration and type for this NUS position?

Initial 12-month fixed-term contract as Research Staff, extendable based on evaluation. Located at Kent Ridge Campus. Open to fixed-term; no salary or visa details specified. See higher ed jobs for contract norms.

💻What technical skills and tools are required for UAV odometry development?

Proficiency in C++ or Python, ROS for real-time systems. Familiarity with PX4 UAV, simulations like Gazebo or AirSim. Knowledge of feature extraction in low-texture, sensor calibration, and embedded platforms like NVIDIA Jetson. Publications in robotics valued. Visit research jobs for tool guides.

📝How to apply and what makes a strong candidate for this role?

Apply via the NUS portal before 2026-06-29. Strong candidates show analytical skills, robotics projects/publications, and communication for research outputs. Experience in world-class research environments preferred. Tailor your CV with free resume template and review research assistant advice.

🔥Are there preferences for non-RGB sensing or challenging environments?

Highly preferred: thermal (LWIR) imaging, event cameras, or non-RGB modalities. Expertise in low-texture/low-SNR conditions, factor graph optimization, or MHE. Ideal for UAVs in smoke, fog, texture-sparse settings. Learn more via related research jobs.

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