Research Position in Electrical Engineering at Nanyang Technological University

Nanyang Technological University, Singapore is inviting excellent students to apply for a master position in computer science. The initial contract for this position is two years. There is no application deadline for this position.

Established in 1981, the SCHOOL OF ELECTRICAL AND ELECTRONIC ENGINEERING (EEE) is one of the founding Schools of the Nanyang Technological University. Built on a culture of excellence, the School is renowned for its high academic standards and research. With more than 150 faculty members and an enrolment of more than 4,000, of which about 1,000 are graduate students, it is one of the largest EEE schools in the world and ranks 6th in the field of Electrical & Electronic Engineering in the 2017 QS World University Rankings by Subjects.

The Rapid-Rich Object SEarch (ROSE) Lab is a research initiative under Nanyang Technological University (NTU). It aims to create a platform for fast mobile searches on object databases. The three key thrusts of the ROSE Lab are: (i) visual object search, (ii) video analytics & deep learning, and (iii) multimedia forensics & biometrics. Resources at the ROSE Lab consist of NTU Faculty, Researchers, PhD Students, and Visiting Scholars & Students from other institutions from around the world. Learn more about ROSE Lab at

The successful applicant will be responsible for the development of human re-identification algorithms, APIs, and toolkits.

(i)Develop an algorithm for human Re-ID across cameras using Deep Networks in the Wild

(ii)Building APIs (Application Programming Interfaces) by using Python or C/C++ to the developed algorithm and testing them for functionality and performance.

The project involves the human re-identification across surveillance cameras, under realistic conditions (different viewing angles, various weather and illumination conditions). Convolutional and/or recurrent neural networks will be employed.

Bachelor degree in Computer Science and/or Engineering.

Expert practical knowledge of state-of-the-art research in human re-id, and/or object recognition in surveillance videos.

Applicant should have technical skills in computer vision and machine learning.

Applicants with experience in deep learning with convolutional and/or recurrent neural networks 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++ and Python.

Experience with deep learning frameworks like PyTorch & TensorFlow, or CUDA programming would be highly beneficial.

Good interpersonal skills, with the ability to work from varied backgrounds.

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

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

Electronic submission of application is highly encouraged.

We regret that only shortlisted candidates will be notified.


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