Research Fellow (Face Recognition, Machine Learning)


The Rapid-Rich Object SEarch (ROSE) Lab is a joint research initiative between the Nanyang Technological University (NTU) and Peking University (PKU).  It aims to create a platform for fast mobile searches on object databases.  The three key thrusts of the ROSE Lab are:  (i) large-scale object database collection and analytics, (ii) scalable mobile object search with contextual mobility, and (iii) media cloud platform.  Resources at the ROSE Lab consist of NTU & PKU Faculty, Researchers, PhD Students, and Visiting Scholars & Students from other institutions from around the world. 

Position Description:

The successful applicant will be responsible for the development of face recognition algorithms, APIs, and toolkits.

This includes:
(i) Develop the face recognition algorithm for surveillance application and social media application by using C/C++.
(ii) Face Database collection for algorithm evaluation, such as images collected from internet
(iii) Building APIs (Application Programming Interfaces) to the face recognition algorithm and testing them for functionality and performance.

The successful applicant will typically be on a 1 year contract basis, with the option to renew based on the candidate’s performance. 

Learn more about ROSE Lab at


• PhD degree in Computer Science and/or Engineering.
• Expert practical knowledge of state-of-the-art research in face recognition.
• Applicant should have technical skills in computer vision and machine learning.
• Applicants with experience with Face Detection and Facial Feature Point Localization are highly preferred.
• Ideally, the applicant should have experience working with large-scale datasets.
• Applicant should be comfortable implementing algorithms in languages such as C/C++.
• Experience on both Windows and Linux platforms, as well as CUDA programming would be highly beneficial.
• Good interpersonal skills, with the ability to work from varied backgrounds. 

Application Procedure:

Interested applicants please attach your full CV, with the names and contacts (including email addresses) of 3 character referees, and all relevant academic certificates to

We regret that only shortlisted candidates will be notified.

Application closes when the positions are filled.

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