博后招募 | 英国伦敦玛丽女王大学袁善欣老师招收博后/博士/实习生/访问学者

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伦敦玛丽女王大学

伦敦玛丽女王大学始建于十九世纪，于1915年加入国际著名的伦敦大学。伦敦玛丽女王大学是伦敦大学四大学院之一，作为国际认可的学术研究型大学，现有2000多名博士生，4600多名教职工 27000名在校学生，其中有近40%是来自于世界各地的国际留学生。历史上有九名诺贝尔奖获得者。在计算机视觉方向有雄厚的研究教学实力及前沿地位。

导师简介

袁善欣（Shanxin Yuan）老师是QMUL电子工程与计算机科学学院助理教授，Digital Environment Research Institute (DERI) Academic lead，此前是华为诺亚方舟实验室伦敦研究所的高级研究员，博士毕业于Imperial College London。老师的研究方向为: computational photography, 3D computer vision, digital human (body, face, hand), neural rendering.

个人主页：

https://shanxinyuan.github.io/

课题组简介

Led by Dr Shanxin Yua, research focuses on computer vision and machine learning, with a strong philosophy of transferring research to significant real-world applications. They work on several lines of research, especially 3D digital humans and computational photography. The recent topics include hand/head/body pose estimation and reconstruction, neural rendering for deformable objects, pose retargeting, immersive gaming, music understanding, and fashion AI. Dr Yuan’s previous research has been successfully shipped to several products that are being used by millions of people worldwide.

博士后申请计划

1. 申请1-2名“玛丽居里学者博士后”（MSCA Postdoctoral Fellowships）；

2. The fellowship offers a 12-24 months’ highly competitive salary and research/training funds, as well as funding to support dependents if required.

3. Open to researchers of any nationality.

4. Research topics: 3D digital humans, neural rendering, computational photography.

申请者要求

1. Hold a PhD degree at the time of the deadline for applications (or have, as a minimum, completed their viva even if not yet awarded).

2. Have a maximum of eight years experience in research, from the date of the award of their PhD degree.

3. Comply with the mobility requirements, including not having resided or carried out their main activity in the UK, or at Queen Mary London University, for more than 12 months in the 36 months immediately before the call deadline (13/09/2023).

Affiliation: Digital Environment Research Institute (DERI)

This is a new research institute at Queen Mary

• Focus on AI, data science, applications of digital technology

• Interdisciplinary research advancing the state-of-the-art

• Excellent facilities (building, computing infrastructure) for AI research

• Events, talks, workshops; strong links with industry