33.1845, Support: English; Computational Linguistics: PhD, TIB – Leibniz Information Centre for Science and Technology

[The LINGUIST List]

LINGUIST List: Vol-33-1845. Wed May 25 2022. ISSN: 1069 - 4875.

Subject: 33.1845, Support: English; Computational Linguistics: PhD, TIB – Leibniz Information Centre for Science and Technology

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Date: Wed, 25 May 2022 23:40:06
From: Jennifer D'Souza [jennifer.dsouza at tib.eu]
Subject: English; Computational Linguistics: PhD, TIB – Leibniz Information Centre for Science and Technology, Hanover, Germany

 Institution/Organization: TIB – Leibniz Information Centre for Science and Technology 
Department: Data Science and Digital Libraries 
Web Address: https://www.tib.eu/en/research-development/research-groups-and-labs/data-science-digital-libraries 

Level: PhD 

Duties: Research
 
Specialty Areas: Computational Linguistics 
Natural Language Processing, Software Engineering 
Required Language(s): English (eng)

Description:

The PhD topics will be in the context of the Open Research Knowledge Graph
(https://www.orkg.org) and the project “SCINEXT - Neural-Symbolic Scholarly
Innovation Extraction”, funded by the Federal Ministry of Education and
Research (BMBF). The aim of these projects is to research and develop
techniques for crowdsourcing, representing and managing semantically
structured, rich representations of scholarly contributions and research data
in knowledge graphs and thus develop a novel model for scholarly
communication. In the context of the PhD thesis you will be responsible for
building and maintaining the ORKG data ingestion and processing pipelines to
ensure the flow of high-quality semantified resources from publications. Your
main responsibility in this position will be to build scalable solutions that
crawl, ingest, process publications, and thereby enrich the ORKG. You will
work alongside the ORKG engineering team to set up the AI/NLP ecosphere.

Your tasks will focus on: 
 - Working in the areas of Natural Language Processing (text mining,
information extraction, information retrieval/search) and Machine Learning of
scholarly communication media (digital) data.
 - Identifying and implementing the tools and algorithms appropriate for
Natural Language Processing assignments to enhance the NLP system currently in
place.
 - Conceptually designing, modeling, and implementing data-driven services for
information retrieval and extraction, data enrichment, and linking of data.
 - Carrying out evaluation experiments and training the developed model.

Please apply via the link below. 

 

Web Address for Applications: https://www.tib.eu/en/tib/careers-and-apprenticeships/vacancies/application-form?Semantic_Web_Technologies%E2%80%9D_%28m%2Ff%2Fd%29_31%2F2022=&tx_powe 

Contact Information: 
	Dr Jennifer D'Souza
	jennifer.dsouza at tib.eu  


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LINGUIST List: Vol-33-1845	
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