Research Associate; Object Detection​/Segmentation

Key Responsibilities

• Develop 3D objects and segmentation models for a robotic pick and place project.
• Develop data augmentation/data synthesis methods to address challenges from limited training data.
• Develop algorithms to annotate 2D images through 3D images.
• Check data quality.
• Review and identify the weaknesses of existing methods for 3D object detection and segmentation.
• Carry out experiments and analyze the results.
• Develop a robotic pick and place with other researchers and engineers.
• Prepare reports and scientific papers.

• Master’s in Computer Engineering, Computer Science, Electronics Engineering or equivalent.
• More than 2 years of research experience preferred.
• In-depth knowledge of deep learning, specifically, 2D and 3D object detection and segmentation, SAM, foundation models, diffusion models, transfer learning and few-shot object detection and segmentation, 3D computer vision.
• Preferably with publications at top AI conferences, such as CVPR, ICCV, ECCV, NeurIPS, ICML and ICRL.
• Strong research capabilities, including innovative thinking, hypothesis formulation, experimental design, and project reporting.
• Collaborative and communication skills, with a proactive, analytical mindset and ability to work independently or as part of a team.
• Preferred technical expertise in software implementation and knowledge of robotics.

Hiring Institution: NTU