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 ([email protected]) or to Adrià de
Gispert ([email protected]). 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.
--
Bill Byrne
Professor of Information Engineering
University of Cambridge
http://mi.eng.cam.ac.uk/~wjb31
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