Postdoc position in ** Computer Vision and Statistical Learning for Human Behavior Analysis **.
LIAMA Sino-French Laboratory in Computer Science, Automation and Applied Mathematics, BEIJING, P.R. CHINA.
French CNRS postdoctororal contract, for two years.
The closing date for application is ** March 30, 2008 **.
The postdoc project is described on: https://www2.cnrs.fr/DRH/post-docs08/?pid=1&action=view&id=596&lang=en
Formal description of the position is available on: https://www2.cnrs.fr/DRH/post-docs08/?pid=8&lang=en
For further information, feel free to contact Franck.Davoine at gmail.com
Applications include a CV and a statement of interest, a link to the Ph.D. thesis, a list of publications, references (names, homepages), in PDF-format, and the formal application form available on https://www2.cnrs.fr/DRH/post-docs08/?pid=1&action=view&id=596&lang=en at the following address:
Dr. Franck Davoine, LIAMA / CASIA, Institute of Automation, Chinese Academy of Sciences, 95, Zhongguancun Dong Lu, PO Box 2728, BEIJING 100080, P.R. CHINA.
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Despite active research in the past decades, robust analysis of facial actions for automatic human behavior understanding in unconstrained environments, as well as non invasive and very accurate capture of subtle facial performances are still very difficult problems, and pose significant research challenges. This is mainly due to the high variability of the face's appearance over time, caused by intrinsic and extrinsic factors such as changes in illumination, out-of-plane rotations, occlusions, facial expressions, etc.
The postdoc position is in the field of human activity and behavior analysis. The successful candidate is expected to participate in the development of novel methods, together with Dr. Franck Davoine, considering richer adaptive models for a better analysis of faces, possibly considering contextual knowledge extracted for example from modalities like body postures or hand gestures. Different focus options are available depending on the interests and strengths of the candidate.
He will be expected to do leading-edge research in the area of computer vision and statistical learning, and be involved in collaborative research projects with academic and industrial partners. He will be employed by the CNRS, and based at the LIAMA Sino-French laboratory in Beijing, P.R.China, during 24 months.
LIAMA is located in the northwestern part of Beijing, in the Haidian science park described as China's Silicon Valley. It offers a very exciting environment for research, a possibility to conduct competitive research and opportunities to cooperate with some of the best groups in China.
Information about the LIAMA is available on http://liama.ia.ac.cn/wiki/
We seek a post-doctoral researcher worldwide. Applicants must have most of the following attributes:
* Excellent computer programming abilities in C/C++/Matlab.
* Proven knowledge and experience of modern computer vision or statistical methods for machine learning.
* A track record of publications in first-rank international computer vision or statistical learning conferences and journals.
* Fluent in English, both written and spoken.
* Creative team player.
LIAMA Sino-French Laboratory in Computer Science, Automation and Applied Mathematics, BEIJING, P.R. CHINA.
French CNRS postdoctororal contract, for two years.
The closing date for application is ** March 30, 2008 **.
The postdoc project is described on: https://www2.cnrs.fr/DRH/post-docs08/?pid=1&action=view&id=596&lang=en
Formal description of the position is available on: https://www2.cnrs.fr/DRH/post-docs08/?pid=8&lang=en
For further information, feel free to contact Franck.Davoine at gmail.com
Applications include a CV and a statement of interest, a link to the Ph.D. thesis, a list of publications, references (names, homepages), in PDF-format, and the formal application form available on https://www2.cnrs.fr/DRH/post-docs08/?pid=1&action=view&id=596&lang=en at the following address:
Dr. Franck Davoine, LIAMA / CASIA, Institute of Automation, Chinese Academy of Sciences, 95, Zhongguancun Dong Lu, PO Box 2728, BEIJING 100080, P.R. CHINA.
--------- ----------
Despite active research in the past decades, robust analysis of facial actions for automatic human behavior understanding in unconstrained environments, as well as non invasive and very accurate capture of subtle facial performances are still very difficult problems, and pose significant research challenges. This is mainly due to the high variability of the face's appearance over time, caused by intrinsic and extrinsic factors such as changes in illumination, out-of-plane rotations, occlusions, facial expressions, etc.
The postdoc position is in the field of human activity and behavior analysis. The successful candidate is expected to participate in the development of novel methods, together with Dr. Franck Davoine, considering richer adaptive models for a better analysis of faces, possibly considering contextual knowledge extracted for example from modalities like body postures or hand gestures. Different focus options are available depending on the interests and strengths of the candidate.
He will be expected to do leading-edge research in the area of computer vision and statistical learning, and be involved in collaborative research projects with academic and industrial partners. He will be employed by the CNRS, and based at the LIAMA Sino-French laboratory in Beijing, P.R.China, during 24 months.
LIAMA is located in the northwestern part of Beijing, in the Haidian science park described as China's Silicon Valley. It offers a very exciting environment for research, a possibility to conduct competitive research and opportunities to cooperate with some of the best groups in China.
Information about the LIAMA is available on http://liama.ia.ac.cn/wiki/
We seek a post-doctoral researcher worldwide. Applicants must have most of the following attributes:
* Excellent computer programming abilities in C/C++/Matlab.
* Proven knowledge and experience of modern computer vision or statistical methods for machine learning.
* A track record of publications in first-rank international computer vision or statistical learning conferences and journals.
* Fluent in English, both written and spoken.
* Creative team player.
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