Nanyang Technological University

Research Fellow (Computer Vision and Object Recognition)

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. 

The successful applicant will be responsible for developing large scale image classification technology at the ROSE Lab. This includes:

  • Developing new algorithms which can achieve good performance on large scale image classification
  • Implementing the algorithms using C++ under the UNIX operation system.
  • Building APIs with industry partners.
  • Adapting the implementation to CUDA to achieve fast speed

 

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

 

Requirement

  • PhD degree in Computer Science or Engineering
  • Excellent background in software engineering with Advanced Programming Skills (C/C++)
  • Experienced in implementing applications for Computer Vision, Object Recognition, and GPU Programming, including knowledge of Matlab, OpenCV, and CUDA.
  • Familiarity with Object Recognition would be strongly preferred.
  • Good interpersonal skills, with the ability to work with people from varied backgrounds.
  • Having publications in top conferences including CVPR and ICCV

 

Application Procedure

Learn more about ROSE Lab at http://rose.ntu.edu.sg/


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:

E-mail Address for E-mailed Applications: WangQ@ntu.edu.sg

Electronic submission of application is highly encouraged.

Only shortlisted candidates will be notified for interview.

Application closes when the positions are filled.

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