30.3896, Jobs: Computational Linguistics; General Linguistics; Semantics: Post Doc, Labex EFL

[The LINGUIST List]

LINGUIST List: Vol-30-3896. Tue Oct 15 2019. ISSN: 1069 - 4875.

Subject: 30.3896, Jobs: Computational Linguistics; General Linguistics; Semantics: Post Doc, Labex EFL

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Date: Tue, 15 Oct 2019 13:09:35
From: Christel Préterre [christel.preterre at sorbonne-nouvelle.fr]
Subject: Computational Linguistics; General Linguistics; Semantics: Post Doc, Labex EFL, Paris, France

 
University or Organization: Labex EFL 
Job Location: Paris, France 
Web Address: http://www.labex-efl.com/wordpress/
Job Title: Post-Doc Text-based Relation Extraction for Knowledge Base Population
Job Rank: Post Doc

Specialty Areas: Computational Linguistics; General Linguistics; Semantics 


Description:

Job title: Text-based Relation Extraction for Knowledge Base Population
Job rank: Post-doc
Duration: 12 months
Job Location: Paris
University/laboratory: LIPN Computer Science Lab
(https://lipn.univ-paris13.fr/en/the-lab/) at Paris 13 University, and ERTIM
NLP lab (http://www.er-tim.fr) at INALCO
Salary: 2000 to 2400 euros per month (according to the applicant's
experience), net of taxes
Application deadline: 20 November 2019
Interview: November 2019
Starting date: 2 January 2020
Contacts for application: Haïfa Zargayouna
(haifa.zargayouna at lipn.univ-paris13.fr) and Kata Gábor (kata.gabor at inalco.fr)

Topic:
Semantic relation extraction is a key component in identifying domain-specific
knowledge in text and structuring it into knowledge bases. While supervised,
neural network based methods (RNNs and CNNs) perform well on domain-specific
relation extraction, this scenario is limited to predefined types of semantic
relations. Therefore, adapting relation extraction to a new domain requires to
have at least a skeleton of a domain ontology with relation types. Our goal is
to further research into acquiring domain-specific relation types and
instances directly from corpora with as minimal supervision as possible. In
previous work, we explored the strengths and limitations of both pattern-based
[1] and DSMbased [2] approaches to unsupervised relation extraction.

Depending on the profile of the candidate, the follow-ups that can be
considered include:
- Improving pattern-based methods for relation extraction,
- Joint entity and relation extraction in specialized domains,
- Unsupervised or weakly supervised relation extraction,
- Knowledge base population with relation instances.

Context:
The post is funded by the Labex EFL project, strand 5: Computational semantic
analysis. The candidate will be jointly affiliated to the LIPN Computer
Science Lab (https://lipn.univ-paris13.fr/en/the-lab/) and the ERTIM NLP lab
(http://www.er-tim.fr).

Selection Criteria:
- PhD in computer science
- Experience and/or interest in:
- Natural language processing
- Text mining and machine learning (experience in deep learning is a plus)
- Knowledge engineering and the semantic web
- Good writing skills

To apply, send the following to Haïfa Zargayouna
(haifa.zargayouna at lipn.univ-paris13.fr) and Kata Gábor (kata.gabor at inalco.fr):
- A detailed CV (with a list of publications)
- A cover letter
- Names and email of two referees



Application Deadline: 20-Nov-2019 
	  
Contact Information:
	Haïfa Zargayouna 
	Email: haifa.zargayouna at lipn.univ-paris13.fr 


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