Application deadline: Thu, 07/17/2014
Employer:University of Girona & Social Currencies Management,SL
The University of Girona and the spin-off Social Currencies Management, SL are looking for a PhD candidate to investigate and develop algorithms on computer vision and social currencies, looking for new ways to monetize the visual content available on the social web.
We offer a three years PhD position with full time salary. This is a good opportunity to explore both, research at academic and industry level at the city of Girona (100km north from Barcelona).
The candidate should have a master degree on computer vision or similar and English proficiency. Experience on basic programming languages (matlab, C, C++, visual C etc.. ) and knowledge on artificial intelligence is also desired.
We are searching for a motivated PhD candidate with a background in machine learning to work on the areas of computer vision and multi-media (recognition, person dentification, attribute learning, weakly supervised learning), sentiment analysis, and internet/web data analytics.
Deadline: 17 July 2014
Start Date: October 2014
For further information please contact Anna Bosch (email@example.com)
To date, the internet has been monetized primarily by text-based ads. In fact, an entire industry has developed around keyword optimization for ad buyers. Words drive SEO. Words drive Google and Facebook ads. Words drive economy of the web. However, it appears that Facebook will now be more show than tell. The shift to a personal newspaper-style format with larger and more prominent photo displays is a response to photo driven behaviour that has rapidly changed the social media landscape. In fact, Facebook CEO Mark Zuckerberg says that 50% of all posts are now pictures, double the amount from just a year ago. As we move toward a visual-centric content universe, the Machines that monetize the internet need to keep up with the times.
We wish to investigate on image intelligence; a way to systematically scan and detect the presence of brand logos, packaging, and products lurking inside the billions of consumer photos streaming into the internet each week; and a way to detect which are the most interesting images for the social users and that can be further used for branding. (According to Facebook, this social network alone gets more than 300 million photo uploads daily). A smart computer vision system applied to those photos could extract the relevant meta-data and essentially turn your friends’ pictures into buyable ad units. You click on the photo and are presented with targeted sales offers.