AI Research Fellow: Automated Cargo Loading & ULD Alignment

SINGAPORE INSTITUTE OF TECHNOLOGY; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

Singapore Institute of Technology seeks a research staff to conduct applied research on AI-enabled multimodal perception for cargo-related systems in a lab environment. The role will develop and validate perception pipelines, integrate with robotic systems, and contribute to technical reports and publications.

You will work with PI/Co-PI and industry collaborators to meet milestones, document methodologies, and support end-to-end demonstrations in realistic mock-up environments.

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical/Electronic Engineering, Robotics, AI, or closely related discipline, with at least three years of relevant work experience; or a postgraduate degree (Master’s or PhD).
• Strong research competence in deep learning and computer vision, with hands-on experience in object detection, segmentation, pose/ alignment estimation, depth perception, 3D vision or multimodal sensor fusion.
• Proficiency in Python and deep-learning frameworks (PyTorch or TensorFlow).
• Experience with RGB-D cameras, depth sensors, ROS/ROS 2, or NVIDIA Isaac Sim beneficial.
• Experience with dataset collection, annotation, synthetic-data generation, experiment design and model validation.
• Strong research record evidenced by publications, reports, patents, open-source software or applied R&D outputs.
• Ability to work with physical robotic systems; safety-critical/aviation/industrial automation exposure advantageous.

Responsibilities

• Participate in and manage research activities with PI/Co-PI to ensure milestones and deliverables are met.
• Define perception scenarios, safety-check criteria, and lighting/occlusion considerations for ULD positioning and CLS lock verification.
• Collect, annotate and curate RGB and depth-sensor datasets with ground-truth labels.
• Develop synthetic-data workflows and digital assets for LDCC, ULD and CLS geometries.
• Design, train and evaluate computer-vision and multimodal perception models for alignment verification and safety assessment.
• Integrate depth sensing and sensor fusion to improve robustness in confined spaces.
• Deploy the perception pipeline in lab and mock-up environments and benchmark against ground truth.
• Document datasets, models, evaluation procedures and results; contribute to reports and publications.

Skills

Deep learning research

Computer vision

Python programming

Experiment design

Technical reporting

Education

Bachelor’s or higher in CS/CE/Robotics

Tools

ROS/ROS 2

NVIDIA Isaac Sim

Job description

Singapore Institute of Technology seeks a research staff to conduct applied research on AI-enabled multimodal perception for cargo-related systems in a lab environment. The role will develop and validate perception pipelines, integrate with robotic systems, and contribute to technical reports and publications.

You will work with PI/Co-PI and industry collaborators to meet milestones, document methodologies, and support end-to-end demonstrations in realistic mock-up environments.