Research Assistant (Object Detection)

Nanyang Technological University; Singapore; On-site; SGD 33,000 - 61,000; Full time

Job summary

Nanyang Technological University (NTU Singapore) invites applications for a Research Assistant to join its university-level research centre collaborating with industry on object detection.

Successful candidates will support data-efficient object detection research, contribute to documentation and potential publications, and perform related duties as required by the project funding body.

Qualifications

• Bachelor’s degree in Computer Science, Electrical/Computer Engineering, or related field (or near completion).
• Basic understanding of machine learning and computer vision principles.
• Familiarity with Python and at least one deep learning framework (e.g., PyTorch, TensorFlow, or Keras).
• Interest in research and willingness to learn and explore new concepts.

Responsibilities

• Participate in lab work and support on data-efficient object detection with key techniques in few-shot learning, transfer learning, image synthesis, etc.
• Assist in preparing technical documentation, reports, and research reports and/or publications as required by the funding body or for dissemination to the wider academic community.
• To undertake any other duties relevant to the programme of research.

Skills

Python

Machine learning

Deep learning

Team collaboration

Communication

Education

Bachelor's degree in CS/EE

Tools

PyTorch

TensorFlow

Keras

Job description

We are seeking a Research Assistant to join a university-level research centre collaborating with industry. Successful candidates will be involved in a project that is related to object detection.

Key Responsibilities

• Participate in lab work and support on data-efficient object detection with key techniques in few-shot learning, transfer learning, image synthesis, etc.
• Assist in preparing technical documentation, reports, and research reports and/or publications as required by the funding body or for dissemination to the wider academic community.
• To undertake any other duties relevant to the programme of research.

Job Requirements

• Bachelor’s degree (or near completion) in Computer Science, Electrical/Computer Engineering, or a related field.
• Basic understanding of machine learning and computer vision principles.
• Familiarity with Python and at least one deep learning framework (e.g., PyTorch, TensorFlow, or Keras).
• Interest in research and willingness to learn and explore new concepts.
• Good communication skills and ability to work both independently and as part of a team.
• Strong motivation, initiative, and a passion for solving technical challenges.

We regret to inform that only shortlisted candidates will be notified.

Hiring Institution

NTU A research-intensive public university, Nanyang Technological University, Singapore (NTU Singapore) has 33,000 undergraduate and postgraduate students in the Engineering, Business, Science, Humanities, Arts, & Social Sciences, and Graduate colleges. It also has a medical school, the Lee Kong Chian School of Medicine, established jointly with Imperial College London. NTU is also home to world-class autonomous institutes – the National Institute of Education, S Rajaratnam School of International Studies, Earth Observatory of Singapore, and Singapore Centre for Environmental Life Sciences Engineering – and various leading research centres such as the Nanyang Environment & Water Research Institute (NEWRI) and Energy Research Institute @ NTU (ERI@N). Ranked amongst the world’s top universities by QS, NTU has also been named the world’s top young university for the past seven years. The University’s main campus is frequently listed among the Top 15 most beautiful university campuses in the world and has 57 Green Mark-certified (equivalent to LEED-certified) buildings, of which 95% are certified Green Mark Platinum. Apart from its main campus, NTU also has a campus in Novena, Singapore’s healthcare district. Under the NTU Smart Campus vision, the University harnesses the power of digital technology and tech-enabled solutions to support better learning and living experiences, the discovery of new knowledge, and the sustainability of resources.

For more information, visit www.ntu.edu.sg