Research Fellow, School of Computing

The National University of Singapore invites applications for the position of Research Fellow in NExT++ Research Centre, School of Computing (SoC). With a strong research interest in the Social Media Analytics, the Research Fellow will work closely with the Lead PI, Prof Chua Tat Seng in carrying out in-depth research to deal with huge volume of real-time rich multi-model data, scalable big data analytics and re-examine the role of man-machine symbiosis at all levels of framework. 

NUS-Tsinghua Centre for Extreme Search (NExT++) is the first of its kind research centre jointly established by the National University of Singapore (NUS) and Tsinghua University of China. When the Centre was started in 2010, it aimed to offer live social media information that is not available on web. NExT had carried out pioneer research on rich media content analytics and search, live social media analytics, and has since built the large-scale systems for live social observatory, wellness and QA. With a dramatic evolution in the social media landscape, NExT++ envisions to empower users through evolving web intelligence. With offering a leading edge big data infrastructure and system, NExT++ will be a hot bed for top quality research and the playground for commercialization and start-ups. 

• A PhD degree in Computer Science/Computer Engineering
• Possess strong background in Mathematics, Algorithms and Social Media Analytics 
• Excellent knowledge in deep learning frameworks, e.g., PyTorch, Tensorflow, Nengo
• Good written and verbal communication skills in English
• Familiarity with non-fully supervised learning
• Result motivated
• Prior publications in major computer vision (CVPR/ICCV/ECCV) or machine learning (NeurIPS, ICML/ICLR) conferences is a plus
• The successful incumbent will be offered an initial one year contract, subject to renewal
   

Only shortlisted candidates will be notified.

Location: Kent Ridge Campus

Organization: School of Computing

Department : Department of Computer Science

Employee Referral Eligible: No

Job requisition ID : 24472