Topic description: In recent years, it has been suggested that statistical approach to spoken dialogue system offer a framework to naturally handle inherent uncertainty in the human speech. The two main advantages of statistical methods are increased robustness in noisy conditions and more natural behaviour learned from data. However, the current methods need large corpora effectively preventing these methods to be used for complex dialogue systems occurring in real-life. The successful PhD candidates will investigate and implement statistical models and methods with the aim of increasing the efficiency of the learning process and reducing the need for large corpora. The conducted research will cover areas of spoken language understanding, dialogue management, and natural language processing.
Skills: Candidates should hold a master degree in a relevant area, such as computer science, mathematics, engineering or linguistics. A strong mathematical background, excellent programming skills (e.g. C/C++, Java, MATLAB, and various scripting languages under Linux environment), aptitude for creative research and autonomy are expected. Experience in machine learning, Bayesian methods, and natural language processing is a plus.
The Institute of Formal and Applied Linguistics is a top-level research group working in the area of computational linguistics and natural language processing. During the fellowship, there will be good opportunities to attend international conferences and workshops. The formal applications should be submitted before June 1. Prospective candidates are strongly encouraged to contact Dr Filip Jurcicek (jurcicek at ufal.mff.cuni.cz) as soon as possible to obtain details about the application process, the institute, and the research opportunities. Additional information is available at http://ufal.mff.cuni.cz/~jurcicek/jobs
Filip Jurcicek Assistant Professor Institute of Formal and Applied Linguistics Charles University in Prague Czech Republic