Research Fellow (Object Detection)

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

Key Responsibilities:

• To independently undertake research on data-efficient object detection with key techniques in few-shot learning, transfer learning, image synthesis, etc.

• To produce research reports and/or publications as required by the funding body or for dissemination to the wider academic community.

• To provide guidance and support to any students associated with the project.

• To attend, contribute, and where necessary lead relevant meetings.

• To undertake any other duties relevant to the programme of research.

Job Requirements:

• PhD degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent.

• Strong background in machine learning and computer vision. Prior experience in data-efficient classification, synthesis, and detection is preferable.

• Strong publication records in top-tier machine learning or computer vision conferences/journals, such as TPAMI, IJCV, CVPR, ICLR, ICCV, ECCV, NeurIPS, ICML.

• Strong coding skills in scientific or engineering software like PyTorch, TensorFlow, Keras, etc.                                                               

• Proven research ability as evidenced through a portfolio of publications and/or conference papers and/or patents.

• Strong background in R&D with self-motivation and initiative. Ability to develop and manage R&D projects with good understanding of industrial needs.

• Strong research and technical expertise in the project domain, including experimental design, modelling methods, prototype system engineering, and laboratory work, with a demonstrated ability to conduct innovative and hypothesis-driven research.

• Collaborative and supervisory capabilities, including assisting in postgraduate supervision, initiating multidisciplinary research collaborations, and overseeing and reporting project progress.

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

Hiring Institution: NTU