Rich experiences in 2D / 2.5D / Video computer vision algorithms covering one of the topics: Video Understanding / Video-based transformer / Video Segmentation.
Solid understanding of state-of-the-arts in Video Understanding and familiar with the challenges of developing algorithms that run efficiently on resource constrained platforms.
Proven prototyping skills and proficient in coding (C, C++, Python).
Candidates with publication record in relevant venues (e.g. NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, SIGGRAPH) are preferred.
Expertise in working with at least one deep learning framework, for example, PyTorch, TensorFlow.
Team oriented, results-oriented, self-motivated and eager to learn new things.
M.S. or PhD in Electrical Engineering/Computer Science or a related field (mathematics, physics or computer engineering), with a focus on computer vision and/or machine learning. Keywords: Video Understanding; Video-based transformer; Video Segmentation
Preferred Qualifications
Excellent written and verbal communications skills, be comfortable presenting research to large audiences, and have the ability to work hands-on in multi-functional teams.