Overview

The Research Group in Computational Linguistics (http://rgcl.wlv.ac.uk)
at the University of Wolverhampton invites applications for TWO 3-year
PhD studentships in the area of translation technology. These two PhD
studentships are part of a university investment which also includes
the appointment of a reader (the equivalent of associate professor) and
a research fellow with the aim to strengthen the existing research
undertaken by members of the group in this area. These funded student
bursaries consist of a stipend towards living expenses (£14,500 per
year) and remission of fees.

We invite applications in the area of translation technology defined in
the broadest sense possible and ranging from advanced methods in
machine translation to user studies which involves using of technology
in the translation process. We welcome proposals focusing on Natural
Language Processing techniques for translation memory systems and
translation tools in general. Given the current research interests of
the group and its focus on computational approaches, we would be
interested in topics including but not limited to:

– Enhancing retrieval and matching from translation memories with
linguistic information
– The use of deep learning (and in general, statistical) techniques in
translation memories
– (Machine) translation of user generated content
– The use of machine translation in cross-lingual applications
– Phraseology and computational treatment of multi-word expressions in
machine translation and translation memory systems
– Quality estimation for translation professionals

Other topics will be also considered as long as they align with the
interests of the group.

The application deadline is 31 July 2017 and the starting date of the
PhD position is 1st October 2017 or any time as soon as possible after
that.

Company:

University of Wolverhampton

Qualifications:

A successful applicant must have:

– A good honours degree or equivalent in Computational Linguistics,
Computer Science, Translation studies or Linguistics
– A strong programming and statistical / Mathematical background or
closely related areas (if relevant to the proposed topic).
– Experience in Computational Linguistics / Natural Language
Processing, including statistical, Machine Learning and Deep Learning,
applications to Natural Language Processing.
– Experience with translation technology

Regardless of the proposed topic experience with programming languages
such as Python, Java or R would be a plus.

Educational level:

Master Degree

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