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Research Associate (Doctoral Student) Natural Language Processing and Scalable Analysis (m/f/d)
GESIS Leibniz-Institut für Sozialwissenschaften
GESIS – Leibniz Institute for the Social Sciences is an internationally active research institute, funded by federal and state governments and member of the Leibniz Association.
Starting on May 1st 2023 our department Knowledge Technologies for the Social Sciences (KTS), Team Big Data Analytics, located in Cologne, is looking for a
Research Associate (Doctoral Student) Natural Language Processing and Scalable Analysis
(Salary group 13 TV-L, working time 75 %, limited to 36 months)
The department Knowledge Technologies for Social Sciences (KTS) conducts research at the intersection of information retrieval, knowledge graphs, human
information interaction and machine learning as foundation for innovative web portals and platforms for the search and use of research data. WTS innovations
are based on a state-of-the-art software stack and research-based innovations in the aforementioned fields.
In the context of the research project NewOrder - Understanding the Erosion of the Traditional Knowledge Order in Scientific Online Discourse and its Impact
in times of Crisis, KTS addresses the challenge of providing Natural Language Processing (NLP) and Machine Learning methods for investigating the effects of
communicating scientific information on social media on society and the research process and vice versa. The research will be conducted in close collaboration
with an interdisciplinary project team including researchers from Psychology, Political and Communication Science.
Your tasks will be:
Applied research in fields such as ML and NLP, specifically with the aim to model and analyse large scale longitudinal online discourse data
Develop NLP and ML methods to predict perceived trustworthiness of scientific online content
Analysis of the generalisability of models, impact of features, and scalability of large language models to study the evolution of concepts, e.g. sentiments
Writing, publishing and presenting project results at intenational conferences
Collaboration with KTS team members and project partners at the Heinrich-Heine University Düsseldorf
GESIS offers an exciting work environment for interdisciplinary research at the interface between social sciences and computer sciences. As an infrastructure institution, we promote social science research cooperate with best-known international research institutes.
GESIS supports your PhD, i.e., with our GESIS Doctoral Program. We offer a wide range of
career possibilities within an attractive working atmosphere with a high degree of responsibility and action possibilities. You work in an international environment in the heart of Cologne. You profit from our ideal working conditions and our internal and external networks.
GESIS is an equal opportunity employer and adheres to the disability guidelines.
We are a family-friendly employer and since 2010 we are certified by the audit Work&Family.
You will find further information here.
University degree (diploma/MSc) in Computer Science, Computational Linguistics or related fields
Research interests in Machine Learning, time series data analysis, NLP
Hands-on experience with Python and handling big datasets, ideally experience with Hadoop and/or SparkNLP
Knowledge of ML-Frameworks such as TensorFlow and PyTorch
Ability to communicate fluently in English mandatory, basic knowledge of the German language desirable
A fast growing and international working environment with a lot of creative scientific freedom and access to unique datasets
Excellent career opportunities in research & teaching as well as in software development and data engineering
Close collaboration and exchange with excellent national and international research labs in Artificial Intelligence and data science
Flexible working hours and the possibility of up to 60% mobile working within Germany
Very good conditions for reconciling work and family life, e.g. subsidies for childcare for children who have not yet attained the age of compulsory schooling
Holistic company health management and discounted participation in the university's sports programme
Generous support for your pension provision as a direct insurance policy
Promotion of your skills through further training measures