PhD position in NLP & Information Extraction at HHU Düsseldorf

Starting now / at the soonest possible date, the Data & Knowledge 
Engineering group at Heinrich-Heine-University (HHU, Düsseldorf), 
affiliated with Knowledge Technologies for Social Sciences (KTS, 
https://www.gesis.org/en/kts) at GESIS (Cologne) and the Computational 
Linguistics department at HHU 
(https://www.ling.hhu.de/bereiche-des-institutes/abteilung-fuer-computerlinguistik) 
are looking for a

*PhD student– Information Extraction & Natural Language Processing*
(Salary group 13 TV-L, working time 75%-100%, initially limited to 36 
months with the possibility of further extension)

In the context of the research project "NewOrder", we are investigating 
scientific online discourse in news & social media, in an 
interdisciplinary consortium involving researchers from Computer 
Science, Psychology, Political and Communication Science. Our research 
will be concerned with novel Natural Language Processing (NLP) methods 
for the analysis of scientific online discourse (e.g. on Twitter) 
addressing challenges arising from its informal nature and 
heterogeneity. For instance, references to scientific works (e.g. 
publications, studies, datasets), scientists or scientific organisations 
are often provided in informal and ambiguous ways. Other challenges 
include the dynamically evolving vocabulary posing challenges for reuse 
and adaptation of both pretrained language models as well as NLP models 
finetuned towards specific downstream tasks. Hence, detecting and 
disambiguating informal science discourse and associated claims remains 
a challenging problem.

Your tasks will be:
*******************
* Research in fields such as NLP, Machine Learning, Language Modeling 
and Representation learning, specifically with the aim to extract 
structured information from online discourse data
* Develop NLP methods for (i) the detection, disambiguation and 
classification of sources of science-related information on social 
media, (ii) assessing the quality and credibility of sources and claims 
and (iii) investigating implicit language cues for cognitive states and 
source characteristics/traits
* Writing, publishing and presenting project results
* Collaboration with team members and project partners in an 
interdisciplinary consortium

Your profile:
**************
* University degree (diploma/MSc) in Computational Linguistics, Computer 
Science or related fields
* Research interests in NLP, machine learning, semantic technologies, 
large language models
* Hands-on experience with Python and handling big datasets, ideally 
experience with Big Data Frameworks (e.g. Spark/Hadoop)
* Knowledge of ML-Frameworks such as TensorFlow and PyTorch
* Ability to communicate fluently in English mandatory, basic knowledge 
of the German language desirable

What we offer:
***************
* Flexible working hours and home office arrangements
* A fast growing and international working environment with a lot of 
creative scientific freedom
* Access to unique research data, (social) web archives and behavioral data
* Support of collaborations with international research labs and experts 
through an extensive international exchange programme

The PhD research will be supervised by Prof. Dr. Stefan Dietze 
(Scientific Director of KTS at GESIS and Professor for Data & Knowledge 
Engineering at HHU) & Prof. Dr. Laura Kallmeyer (Chair of Computational 
Linguistics department at HHU).

For further information please contact Stefan Dietze 
(stefan.dietze@hhu.de) and/or Laura Kallmeyer 
(kallmeyer@phil.uni-duesseldorf.de).

Interested?
*************
Please apply by sending your complete application documents as a single 
PDF file to stefan.dietze@hhu.de by 20 December 2023.


-- 
Prof. Dr. Stefan Dietze

Scientific Director Knowledge Technologies for the Social Sciences
GESIS - Leibniz Institute for the Social Sciences
Web: https://www.gesis.org/en/kts

Professor of Data & Knowledge Engineering
Heinrich-Heine-University Düsseldorf
Web: https://www.cs.hhu.de/en/research-groups/data-knowledge-engineering

Member at L3S Research Center
Web: http://www.l3s.de

Phone: +49 (0)221-47694-421
Web: http://stefandietze.net

Received on Thursday, 23 November 2023 17:22:00 UTC