P-Sphere (COFUND project) Postdoc Position in Advanced reading systems – 2nd call open in September 2016
The second call of the program will open in September 2016. For further information please, refer to the official webpage of the call: http://www.uab.cat/psphere/Topic Title: Advanced reading systems
Topic description (*)
The successful candidate will work on unconstrained reading systems, capable to detect and recognise textual information in challenging conditions such as urban scenery, born-digital images, videos and images recorded with wearable devices etc.
The selected candidate is expected to align his research to the research priorities of the host group. Of particular interest is the interplay between visual and textual content in an urban scene image, and to what extent such modalities can work synergistically towards urban scene imagery interpretation. Interaction with textual content and camera-based capture and analysis of document images are also of interest.
The selected candidate is expected to develop his research plan in one or more of the following areas: scene text localisation, object proposals for text, script identification, word spotting, language models, deep network architectures for robust reading, camera-based document image analysis, and human-document interaction among others.
Project supervisor & hosting group
The selected candidate will join a vibrant team of six researchers pertaining to recognised Consolidated Research Groups (SGRs) within the Catalan research system, with background on pattern recognition, reading systems, scene classification and object recognition. The hosting team is widely recognised in its areas of research: robust reading systems, object recognition and scene interpretation.
The activities of the team take place within the Computer Vision Centre, a research institute comprising more than 100 researchers and support staff, dedicated to computer vision research and knowledge transfer.
The activities of the team are supported by multiple research and technology transfer projects.
The host team is collaborating with a number of institutions world-wide. The research fellow will have the opportunity to participate actively in these collaborations, including through research stays.
A PhD in computer science or a related field is required.
The applicants must have experience in pattern recognition and machine learning techniques, and be able to demonstrate strong analytical and programming skills.
Prior research and publications on areas such as scene text localisation, object proposals for text, script identification, word spotting, language models, and character recognition would be highly valued.
The applicants are expected to be fluent in both oral and written communication in English. They should work well in a team, while demonstrating initiative and independence.