10 July: fyi -- phd funding, France
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PHD STUDENTSHIP in NATURAL LANGUAGE GENERATION
Starting date: Fall 2014
Duration: 3 years
Deadline for Application: Open until Filled
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The Research Group in Computational Linguistics, Synalp/LORIA in Nancy
(France) invites applications for a three-year-funded PhD studentship in
Computational Linguistics.
Theme: Data-to-Text Generation
Main topic: Natural Language Generation for the Semantic Web
Description: There is a growing need in the semantic web (SW) community
for technologies that give humans easy access to the machine-oriented Web
of data. Because it maps data to text, Natural Language Generation (NLG)
provides a natural mean for presenting this data in an organized, coherent
and accessible way. Conversely, the representation languages used by the
semantic web (e.g., OWL ontologies and RDF data) are a natural starting
ground for NLG systems. The aim of the PhD thesis will be to explore the
interaction between the semantic web, the textual web and Natural Language
Generation (NLG). More precisely, the goal will be to develop generic
weakly supervised methods for generating text from semantic web data in
particular, content selection and verbalisation methods.
The project will build on an ongoing collaboration between LORIA (Nancy,
France), the KRDB group at (Bolzano, Italy) and Stanford Research
International (USA), bringing together high level academic partners with
internationally recognised expertise in both NLG (LORIA) and knowledge
processing (KRDB, SRI).
Profile: We are looking for outstanding young research scientists with a
good honours degree in Computational Linguistics or Computer Science, with
programming skills and with a strong interest in Natural Language
Processing.
Required skills:
- Master's degree in Computational Linguistics or Computer Science
- experience in Natural Language Processing
- good command of the English language
Desirable skills:
- experience in natural language generation
Supervisor:
- Claire Gardent, http://www.loria.fr/~gardent/
Research Environment: LORIA is a computer science research unit which
conducts most of its scientific activities in partnership with the Inria
Nancy - Grand-Est Centre, the French National Centre for Scientific
Research (CNRS), the University of Lorraine. We also maintain close ties
with research institutes and universities from the wider region, notably in
Saarbrücken and Luxembourg. With around 500 staff and 27 research teams, it
is one of the biggest research unit in Lorraine. It conducts research in
Algorithms, Computation, Image & Geometry; Formal methods; Networks,
Systems and Services; Knowledge & Natural Language Processing; and Complex
Systems & Artificial Intelligence.
The PhD will be funded by the ITEA3 ModelWriter project (
https://itea3.org/project/modelwriter-1.html) for a period of 36 months.
Including industrial and academic partners from France, Belgium and Turkey,
this projects targets the Development of an integrated authoring
environment combining a semantic parser, a data-to-text generator and
Knowledge Capture Tools.
The PhD Candidate will be working in collaboration with the members of the
Synalp team (http://talc1.loria.fr/synalp/stories/about.html), a Research
Group in Computational Linguistics. Synalp research focuses on hybrid,
symbolic and statistical approaches to natural language processing and
applications built thereon, including NLP for Man-Machine Dialog, for
language learning and for Data Verbalisation.
Location: Nancy (http://en.nancy-tourisme.fr/) is a high-tech city located
at the heart of the Lorraine Region, in outstanding scientific and natural
surroundings. It is 1h30 by train from Paris, Germany and Luxemburg and 1h
from Paris Roissy international airport.
To apply, please send CV, Transcripts of Records for Master degree and
either Reference letters or Referee names to :
Claire Gardent, claire.gardent@loria.fr
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Claire Gardent
Tel. +33 3 83 59 20 39
Fax +33 3 83 41 30 79
http://www.loria.fr/~gardent
LORIA UMR 7503
Equipe SYNALP, Bat. B
615, rue du jardin botanique
54600 Villers lès Nancy
France
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