Nanyang Technological University

Research Fellow (Machine Learning, Image Classification)

Background:

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:

The successful applicant will be responsible for the development of large scale image classification systems using machine learning techniques.  This includes:

(i) Building image classification systems, including parallelising and optimising the algorithms developed by other ROSE Lab researchers.

(ii) Working with industry partners of the ROSE Lab to test the classification systems.

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 http://rose.ntu.edu.sg/

 

Requirements:

• PhD degree in Computer Science & Engineering.

• Must have at least 5 years’ experience in C/C++

• Must be familiar with CUDA and OpenCV programming

• Must be familiar with the Linux programming environment.

• Must have research experience in image processing and image classification.

• Must have publications in top image analysis journals and conferences. 

 

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 WangQ@ntu.edu.sg

We regret that only shortlisted candidates will be notified.

Electronic submission of application is highly encouraged.

Application closes when the positions are filled.

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