Research Associate: Computer Vision & ML

Nanyang Technological University Singapore; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

Nanyang Technological University Singapore (NTU Singapore) invites applications for a Research Associate in the College of Computing and Data Science (CCDS). The RA will support cutting-edge projects in computer vision, machine learning, physical AI, and spatial AI, contributing to the development of algorithms, data pipelines, and experimental evaluations.

Reporting to the Principal Investigator, you will collaborate with faculty, postdoctoral researchers, and PhD students to bridge

Qualifications

• Hold a Master degree in Computer Science.
• Sufficient knowledge of deep and statistical learning methods.
• Excellent communication for publications and presentations.
• Independent, analytical, proactive and a team player.
• Strong publication record at major conferences preferred.

Responsibilities

• Conduct individual research within the designed project: process data, develop methods, and evaluate algorithms.
• Author research articles for peer-reviewed conferences.
• Engineer software based on research outcomes and share on the group’s web.
• Manage own academic research and administrative activities.
• Adapt existing and develop new scientific techniques and protocols.
• Test hypotheses and analyze scientific data from diverse sources.
• Contribute ideas for new research projects and proposals.
• Assist in developing ideas for generating research income.

Skills

Deep learning

Statistical learning

Computer vision

Machine learning

Research

Communication

Education

Master degree in Computer Science

Tools

Python

PyTorch

TensorFlow

MATLAB

Job description

Nanyang Technological University Singapore (NTU Singapore) invites applications for a Research Associate in the College of Computing and Data Science (CCDS). The RA will support cutting-edge projects in computer vision, machine learning, physical AI, and spatial AI, contributing to the development of algorithms, data pipelines, and experimental evaluations.

Reporting to the Principal Investigator, you will collaborate with faculty, postdoctoral researchers, and PhD students to bridge