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.
