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新加坡科技设计大学赵娜老师（个人主页https://na-z.github.io）求贤纳士！主要研究方向：3D Computer Vision。现提供全额奖学金博士名额，并招募全职研究助理 (research assistant) 及带薪研究型实习生 (research intern)！欢迎有志于在计算机视觉及机器学习研究领域深造的同学加入团队！导师/学校简介： Dr. Zhao Na is an assistant professor at University of Singapore, supervised by Prof. Chua Tat-Seng and Associate Prof. Gim Hee Lee. She is Information Systems Technology and Design (ISTD) pillar, received her PhD from National a very active researcher in the 3D scene understanding field. Her works have Singapore University of Technology and Design (SUTD). She published at top-tier computer vision and machine learning conferences such as CVPR, AAAI, ECCV, etc. She has served as the invited reviewer for top-tier conferences including CVPR, ICCV, ECCV, AAAI, IJCAI, and ACMMM. Introduction to SUTD: Established with MIT in 2010, SUTD is Singapore's fourth public-funded university, which aims to advance knowledge and nurture technically grounded leaders and innovators to serve societal needs. In 2017, SUTD was ranked by Clarivate Analytics as the 5th most influential scientific research university in telecommunications and the 6th in electrical engineering research in the world. According to the "Global state of the art in engineering education" report released by MIT in 2018, SUTD was selected as the "Top 10 emerging leaders in engineering education" in the world and ranked 1st. Research Interest: Dr Zhao’s research interest lies in the interdisciplinary field of scene understanding and machine learning, aiming to enable intelligent machines to perceive the real-world environments with comprehensive scene understanding that ultimately leads to fully autonomous intelligent machines. Her previous representative works including semi-supervised 3D object detection, few-shot 3D semantic segmentation, and class-incremental 3D object detection, are all the first explorations in the interdisciplinary field. Her current and future research focus on: 1) data-efficient 3D scene understanding including semi-supervised, few-shot, zero-shot, self-supervised learning; 2) multi- modal joint learning for scene understanding with images and point clouds; 3) out-of-distribution learning (e.g., domain adaptation, domain generalization) for (3D) scene understanding; 4) robust learning with noisy labels for (3D) scene understanding; 5) sequential point cloud learning; 6) online 3D scene understanding that reconstructs and understands 3D scenes simultaneously. Open positions: Dr Zhao is looking for motivated PhD students and research assistants/interns to work on the above research topics. - Ph.D. students with applicable scholarships/fellowships: o SUTD Fellowship o AISG Fellowship o AGS Scholarship o ACIS Scholarship o SDGF Fellowship (open to Singapore citizens only) o SINGA Scholarship (open to international students only) - Full-time research assistants: o Monthly salary: $3500-4000 - Full-time research interns (at least 6-month visiting): o PhD: $2000-2500 o Master: $1500-2000 o Undergraduate: $1000-1300 Essential Requirements: - Bachelor or master’s degree in Computer Science or a closely-related discipline with high academic standing - Competent in at least one programming language (C/C++ or Python) - Expertise in deep learning framework(s) such as pytorch and tensorflow - Experience in computer vision or machine learning, someone with related publication(s) on top conferences/journals is preferred - Fluent in written and spoken English - Self-motivated and enthusiastic about doing impactful research Contact: Please drop an email to na_zhao@sutd.edu.sg with your CV, transcript(s), and research statement (1-2 pages) that describes your experience and your interested research topic.

新加坡科技设计大学(SUTD) CV(3D) PhD,RA,Intern 招生帖