PhD student– Information Extraction & Natural Language Processing
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-computerlingu...) 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, data mining, 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.