Dottorato in Tecnologie per la traduzione (Unv. di Wolverhampton, UK): opportunità

    2 PhD studentships in Translation Technology
                          Closing date 31st July 2017
    The Research Group in Computational Linguistics (
    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
    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.
    Applications must include:
    1. A curriculum vitae indicating degrees obtained, courses covered,
    publications, relevant work experience and names of two referees that
    could be contacted if necessary
    2. A research statement which outlines the topics of interest. More
    information about the expected structure of the research statement can
    be found at 
    These documents will have to be sent by email before the deadline to
    Amanda Bloore ( Informal enquiries can be sent to
    Constantin Orasan ( 
    The shortlisted applicants will be interviewed by phone/Skype shortly
    after the application deadline. 
    Established by Prof Mitkov in 1998, the research group in Computational
    Linguistics delivers cutting-edge research in a number of NLP areas.
    The results from the latest Research Evaluation Framework confirm the
    research group in Computational Linguistics as one of the top
    performers in UK research with its research defined as ‘internationally
    leading, internationally excellent and internationally recognised’. The
    research group has recently completed successfully the coordination of
    the EXPERT project a successful EC Marie Curie Initial Training Network
    promoting research, development and use of data-driven technologies in
    machine translation and translation technology (
    Pubblicato il 5 luglio 2017