PhD student position in Statistical Machine Translation at ILLC

For the STW-funded project "Data-Powered Domain-Specific Translation Services On Demand" led by Dr Khalil Sima'an, the ILLC is looking for a PhD student in Hierarchical Statistical Machine Translation.

The DatAptor project aims at research and development for advanced statistical machine translation (SMT) systems that adapt to a new domain automatically using algorithms for extracting and weighting suitable training instances in an industry-scale, multi-domain parallel corpus. The project addresses various challenges including statistical weighting of parallel data instances to better fit user-supplied example documents, SMT adaptation by-example to new domains, and extensions of hierarchical and syntactic SMT systems. The PhD student is expected to work among others on the latter topic, i.e., hierarchical (and syntax-enriched) SMT systems.

The closing date for application is 12 October 2012. Vacancy number: W12-185. For more information, see http://www.uva.nl/over-de-uva/werken-bij-de-uva/vacatures/item/w12-185.html or contact Dr Khalil Sima'an at k.simaan at uva.nl.