The Intelligent Systems Lab Amsterdam (ISLA) of the University of Amsterdam offers a 4 year PhD position in the field of computer vision and machine learning. The topic of the PhD is to recognize objects in a visual data stream. In such a stream the object classes of interest shift over time. Hence, the traditional approach to learn classifiers for a predefined set of objects is unsuited. A promising approach in classifying unseen objects into a novel category is to learn a semantic attribute image representation. The aim for this PhD is to develop new algorithms to learn such a high-level semantic representation from weakly annotated images and to learn the mapping to an unknown class from freely available (textual) sources. Another project aim is to model the visual data stream to understand which images or novel concepts could become a visual trend.
The position is within the Intelligent Systems Lab Amsterdam (ISLA) and will be supervised by dr. Thomas Mensink and dr. Cees Snoek. The position is part of a 5-year Personal VIDI Grant funded by the Dutch Organization for Scientific Research. The successful candidate will work in a stimulating environment of a leading and highly active research team including one faculty member, a post-doc and six PhD students. The team has repeatedly won the major visual search competitions, including NIST TRECVID, PASCAL Visual Object Challenge, ImageCLEF, and the ImageNet Large Scale Visual Recognition Challenge. Requirements - Master degree in Artificial Intelligence, Computer Science or related field; - Excellent programming skills (the project is in Matlab, Python and C/C++); - Solid mathematics foundations, especially statistics and linear algebra; - Highly motivated; - Fluent in English, both written and spoken; - Proven experience with computer vision and/or machine learning is a big plus. Additional Information http://www.uva.nl/over-de-uva/werken-bij-de-uva/vacatures/item/13-205.html Kind regards, Thomas Mensink [email protected] _______________________________________________ uai mailing list [email protected] https://secure.engr.oregonstate.edu/mailman/listinfo/uai
