A one-year postdoctoral position in sentiment analysis is available at the CIMeC/CLIC laboratory of the University of Trento (http://clic.cimec.unitn.it/) starting as soon as possible from January 2013. The fellowship has a duration of 1 year.
The successful candidate will join a team of computational linguists and cognitive neuroscientists using machine learning methods to extract information about the polarity of words (positive / negative) from recordings of neural activity (EEG, MEG and fMRI). The main focus for this particular position will be the Deep Relations project, a collaboration between CIMEC, Cogito / Expert Systems and Fondazione Bruno Kessler (FBK). The role of the postdoc in the project will be to develop methods using brain-derived word polarities to assess the overall polarity of the text, and to compare these polarities with those computed using traditional lexical resources for sentiment analysis such as WordNet Affect or SentiWordnet.
The ideal candidate for the position is a researcher with a PhD in computer science / electronic engineering, cognitive science / cognitive neuroscience, or linguistics, with focus on Human Language Technology and ideally a strong research background in sentiment analysis or statistical methods in Human Language Technology. Familiarity with machine learning and programming skills are a must.
The Language Interaction and Computation Lab (CLIC) is a unit of the University of Trento's Centre for Mind/Brain Sciences (CIMEC) (www.cimec.unitn.it): an interdisciplinary Centre for the research in brain and cognition including neuroscientists, psychologists, (computational) linguists, computational neuroscientists, and physicists. CLIC consists of researchers from the Departments of Computer Science and Cognitive Science carrying out research on a range of topics, including concept acquisition and information extraction from very large multi-modal corpora, combining brain data and data from corpora to study cognition, and theoretical linguistics.
For additional information please contact Massimo Poesio (massimo.poesio at unitn.it), attaching your CV.