XRCE Internship: Optimization and Sampling Techniques for Statistical Machine Translation
Start Date : Around June 2012
Duration : 4-5 months
The MLDAT area (Machine Learning for Document Access and Translation) at XRCE (Xerox Research Centre Europe) is opening an internship to pursue its current research line in Optimization and Sampling Techniques for Statistical Machine Translation.
XRCE has developed some algorithms, which combine optimization and sampling in novel ways in order to perform inference and training for a number of NLP tasks, in the presence of complex feature spaces.
We are looking for a motivated intern to pursue this line of work, further implement these techniques and perform experiments in the context of phrase-based and/or syntax-based translation.
The successful candidate should be enrolled in a graduate program, at the Master or (preferably) PhD level, with focus on Machine Learning, Optimization, Statistical NLP, or (ideally) Statistical Machine Translation.
Strong programming skills (one or several of C/C++, Python, Java…) are a requirement.
IMPORTANT. Priority will be given to students who are members of institutions affiliated to the PASCAL-2 network of excellence. A partial list of such institutions is available at: http://pascallin2.ecs.soton.ac.uk/Network/Sites .
For further details, please contact Marc Dymetman (firstname.lastname@example.org).