PhD Candidate in Computational Linguistics (Natural Language Processing)

     
Employer
Published
WorkplaceFlemish Region, Ghent, Belgium
Category
Position

Description

PhD candidate in Computational Linguistics (Natural Language Processing)

Job description

In the context of a research infrastructure project, a scholarship is offered for a PhD candidate in the LT3 Language and Translation Technology Team at the Ghent University Department of Translation, Interpreting and Communication. The successful applicant will participate in a multidisciplinary research collaboration between UGent (?iaLing and LT3) and UHasselt (Expertise Centre for Digital Media). The PhD research topic is part of a Hercules (FWO-funded) project (see description below), and focuses on the extension of Natural Language Processing tools for application in the domain of Spanish dialectology.

The successful candidate is appointed for two years. Further funding will be sought for the remainder of the PhD project. The starting date is as soon as possible.

Description of the Hercules project:

The study of dialectal microvariation of Spanish spoken in Spain has until recently mainly focused on lexical and phonetic features. The morphosyntax of these dialects, on the contrary, remains largely unexplored, despite the recent surge in interest in dialect grammars. This is due to the lack of large annotated dialectal corpora. This project aims to fill this lacuna and will create the first morphosyntactically annotated and parsed corpus of the European Spanish dialects. This dialect corpus will be designed in a geographically balanced way and its material will proceed from the COSER corpus (Corpus Oral y Sonoro del Espaņol Rural ’Audible Corpus of Spoken Rural Spanish’; ?url=www.corpusrural.es&module=jobs&id=1331" target="_blank" rel="nofollow">www.corpusrural.es), which is the largest collection of oral data in the Spanish-speaking world. As transcribing and annotating are expensive and labour-intensive, this project takes a collaborative game-based approach to building the parsed corpus of European Spanish dialects. In other words, a crowdsourced game will be built through which members of the public contribute to the co-creation of the parsed corpus by providing annotations in the context of a game.

Profile of the candidate

Requirements:

  • Master’s degree in a relevant field ((Computational) Linguistics, (Computational) or Computer Science)
  • Strong interest in language and speech technology
  • Interested in research and having the intention to obtain a PhD degree
  • Fluent /(near) native in Spanish and English
  • Strong interpersonal and communication skills
  • Eager to acquire new competences and knowledge
  • Knowledge of programming languages (e.g. Python, Java)
  • The candidate should be able to work independently as well as in a multidisciplinary team, and will be guided by advisors with a computer science/computational linguistics background (UGent-UHasselt) and with a background in dialectology / linguistics (UGent).


How to apply

The application in English should include

  • a motivation letter, summarizing the candidate’s background and capabilities, and describing his/her motivation for this position
  • attested copies of education certificates, and a list of master courses with the grades obtained
  • contact information (e-mail) of potential referees


 

Applications are to be sent by e-mail to Prof. Dr Veronique Hoste ( Veronique.Hoste [at] UGent[.]be ) and Prof. Dr Miriam Bouzouita ( Miriam.Bouzouita [at] UGent[.]be ).

Application deadline: February 7th, 2019.

Those who have applied previously do not need to resubmit their application as they will be considered.

 

Contact persons for more information:

  • For general information about the Hercules project: Prof. Dr Miriam Bouzouita (Principal Investigator) ( Miriam.Bouzouita [at] UGent[.]be ); 
  • For specifications about this post: Prof. Dr Veronique Hoste ( Veronique.Hoste [at] UGent[.]be )

Web

In your application, please refer to myScience.be
and reference  JobID 1331.