[Elsnet-list] Two-year Post-doc, Cambridge University, Statistical Machine Translation
bill.byrne at eng.cam.ac.uk
Tue Jul 15 20:53:11 CEST 2014
A Research Associate (Post-Doctoral Researcher) position in Statistical Machine Translation will be available at the University of Cambridge.
The Research Associate will be funded by the recently awarded EPSRC (UK) project `Improving Target Language Fluency in Statistical Machine Translation'. The project will focus on developing robust, natural language generation systems that can be incorporated directly into syntax-based SMT.
Duration: 24 months, starting Summer or Fall 2014. A second 2-year position will become available in mid-2015.
Deadline: The positions will remain open until filled.
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
- Natural language generation
- Statistical language modelling
- Translation grammars for syntactic SMT
- WFST algorithms and modelling techniques
- `Big Data' techniques large-scale text processing and for machine learning (e.g. MapReduce, Hadoop)
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.
Please send your CV to Bill Byrne (bill.byrne at eng.cam.ac.uk) or to Adrià de Gispert (ad465 at cam.ac.uk). We are happy to answer any questions related to the position or the project.
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 under the direction of Professors Mark Gales, Phil Woodland, and Steve Young. 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).
See Cambridge Language Sciences (www.languagesciences.cam.ac.uk) for an overview of language research at the University of Cambridge.
Professor of Information Engineering
University of Cambridge
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