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摄影测量,计算机视觉博士,博士后职位开放

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招生
学校名称: 俄亥俄州立大学
专业: CS
入学年度: 2023
入学学期: Spring
导师个人主页: https://u.osu.edu/qin.324/opportunities/

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实验室微信公众号原文连接:
https://mp.weixin.qq.com/s/_VrKMAv7o4MWRLr4AY_96w

小组职位开放, 欢迎大家申请,推荐,转发 - 俄亥俄州立大学 (摄影测量,计算机视觉)
If you are enthusiastic to work at the conjunction of Computer Vision and Geomatics, a few funded Ph.D./Postdoc Positions are available in our group at The Ohio State University. We are solving view rendering, generation, registration challenges with geospatial fidelity at all levels. Research are in collaboration with computer vision groups at multiple institutes (SRI, MIT, UCI, USC etc. ), on monthly basis.
Degree registration follows a general principle listed under our page here (https://u.osu.edu/qin.324/opportunities/) (sourcelink). Positions can start immediately. If you are interested, please email Dr. Qin (qin.324@osu.edu) your CV that best describes yourself in alignment with qualification specified as follows. We embrace teammates who are critical thinker, quick learner, actionist, committed team player, please do not be shy to mention that in your email if you consider yourself highly in these aspects.
Education:
Computer science, Geomatics, Strong in Programming and Math
Field:
Computer Vision, Photogrammetry, Vision-based Machine Learning
Preferred skillsets (prioritized in order):
1. Proficient in Structure from Motion/Photogrammetry/Multi-view image matching, error modeling.
2. Experiences in Neural Radiance Field and GAN, Diffusion Models.
3. Experience in Intrinsic Image Decomposition, Inverse Rendering.
4. Experience in Satellite Photogrammetry and sensor modeling.
5. Student with a master’s degree preferred, ok with a bachelor’s degree if you consider yourself competitive.
Preferred+:
1. Master in C++, ability to work across different coding languages to build workflow.
2. Have one or more good publications that you are a major contributor to
3. Good communication/writing skills.

上一篇:美国犹他大学分子影像和生物材料方向招收全额奖学金博士、博士后以及访问学者
下一篇:美国新泽西理工学院(NJIT)招收2-3名全奖PHD (Trustworthy AI/数据挖掘/机器学习)
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