Postdoctoral Position in the Vision and Learning Lab, University of Alberta

WorkplaceToronto, Alberta, Canada

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Frequently Asked Questions

Postdoctoral Position in the Vision and Learning Lab, University of Alberta

Electrical & Computer Engineering

We are setting up a new lab at the ECE Department, University of Alberta, focusing on exciting research topics in computer vision and machine learning, such as geometric methods for computer vison and machine learning problems, visual behavior analysis, and biomedical image analysis. We are looking for exceptional Postdocs to join us. Ideally, you are a PhD with demonstrated ability to conduct high quality research in computer vision and/or machine learning, and have a track record of publications in top venues. The start date is flexible. The position is for 1-2 year(s) with possibility for renewal.

Potential candidates are requested to email their CVs (in PDF) and contact information of at least two references to Li Cheng (

About the PI

Li Cheng is an associate professor with the ECE Dept., University of Alberta, Canada. His research expertise is mainly in computer vision and machine learning, with application focus in both visual behavior analysis and biomedical image analysis. His research work has resulted in over 80 referred papers including those published at journals such as IEEE Trans. Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, as well as conferences such as ICML, NIPS, ICCV, CVPR, MICCAI, and AAAI. He is a senior member of IEEE. More information is available here .

We thank all applicants for their interest; however, only those individuals selected for an interview will be contacted.

The University of Alberta is committed to an equitable, diverse, and inclusive workforce. We welcome applications from all qualified persons. We encourage women; First Nations, Métis and Inuit persons; members of visible minority groups; persons with disabilities; persons of any sexual orientation or gender identity and expression; and all those who may contribute to the further diversification of ideas and the University to apply.
In your application, please refer to and reference JobID 1153775.