PHD Trainee Program (Required Master Degree)

• Fully-Funded PhD Positions - Synthetic Data Generation
• Fully-Funded PhD Positions - Agentic AI & Edge Computing
• Fully-Funded PhD Positions - Small Multimodal Models

Reolink via Industrial Postgraduate Programme (IPP)

• We currently have three research topics available for postgraduate students interested in exploring these opportunities.

About Reolink

Reolink is a leading AI video security camera firm based in Singapore, driving innovation in intelligent visual technology for both home and business. Founded in 2009, our products are trusted by millions of users across more than 110 countries. At the forefront of smart surveillance, Reolink develops cutting-edge unified AI systems-such as Reon Eura-engineered to deliver superior on-device object recognition, predictive risk assessment, and intelligent contextual analysis. We are committed to pushing the boundaries of edge computing, computer vision, and autonomous AI to create the next generation of reliable, user-centric security applications.

Programme Structure (IPP) Successful candidates will be full-time salaried employees at Reolink (the partnering company) while simultaneously pursuing full-time graduate studies (PhD) at NTU & NUS. Reolink is a rapidly growing tech company with strong international presence.

This unique arrangement offers:

• Competitive monthly salary + full PhD tuition coverage.
• Hands-on industry experience alongside academic research.
• Joint supervision by NTU / NUS faculty and Reolink R&D leaders.
• Direct application of research to real-world AI and computer vision products.

Opportunity for Postgraduate individual that eager to pursue a PhD while simultaneously maintaining a full-time position in the industry.

• Candidates must be strong in software engineering

• A Bachelor's degree or Master's in Computer Science, Software Engineering, Computer Engineering, or a related field.
• Excellent programming skills ( Python, C++ and deep learning frameworks such as PyTorch / TensorFlow).
• Solid understanding of software design, system integration, and deployment best practices.
• Strong analytical and mathematical foundation.