About this role
A Research Associate (Post-Doctoral Researcher) position in Statistical Machine Translation is available at the University of Cambridge.
The Research Associate will be funded by the EPSRC (UK) project `Improving Target Language Fluency in Statistical Machine Translation’. The project is focused on developing robust, natural language generation systems that can be incorporated directly into syntax-based SMT.
For candidates with an interest in supervision of graduate research, there will be opportunities to set and lead research projects on the new Cambridge MPhil in Machine Learning, Speech, and Language Technologies which will begin in October 2015.
SMT at Cambridge (http://divf.eng.cam.ac.uk/smt):
Cambridge SMT researchers have developed the HiFST/HiPDT translation systems (http://ucam-smt.github.io), leading to the 2012 EAMT Best Paper and EAMT 2010 Best Thesis awards. The team participates in international MT evaluations, such as the NIST and WMT shared tasks, with entries consistently ranked among the top submitted systems. Cambridge SMT researchers also have strong industrial connections, with PhD students and RAs going on to take positions at Google, IBM, SDL, Facebook, Nuance, and other top research labs in the UK and USA.
The SMT research team is part of the Cambridge Speech and Language Technologies Group which also carries out research in speech recognition, speech synthesis, and statistical dialogue systems. The SLT Group also has strong collaborative ties to the Natural Language Processing group at the Cambridge Computer Laboratory (http://www.cl.cam.ac.uk/research/nl/) and to the Cambridge Computational and Biological Learning Group (http://cbl.eng.cam.ac.uk).
Company:
University of Cambridge
Qualifications:
Candidates should have a Ph.D. in machine learning, natural language processing, speech recognition, or a related area, with interests in any of the following topics :
– Statistical machine translation, syntactic SMT
– Neural networks, deep learning
– Natural language generation
– `Big Data’ techniques large-scale text processing and for machine learning (e.g. Hadoop, Spark)
Specific requirements:
Duration: 12 months, renewable for another 12 months, starting Summer or Fall 2015.
Educational level:
Ph. D.