Student Research Assistant, Team Transparent Social Analytics (SHK-CSS-39)

GESIS; Köln; Ibrido; EUR 18.000 - 26.000; Part-time

Vantaggi offerti da questo lavoro

Flexible working hours

Mobile working options

Interdisciplinary environment

Thesis opportunities

Health management benefits

Professional development

Descrizione del lavoro

GESIS – Leibniz-Institute for the Social Sciences in Cologne invites applications for a Student Research Assistant in the Computational Social Science (CSS) department, Team Transparent Social Analytics. The role offers up to 10 hours per week with a temporary contract and an hourly wage of 16.09 €.

You will evaluate literature, help build pipelines for automated disinformation detection on large text corpora using ML models and LLMs, and support manual annotation of smaller datasets.

Competenze

• Enrollment in a bachelor’s or master’s program in sociology, political science, communication, linguistics, computer science, data science, or related discipline.
• Proficiency in Python, or proficiency in R with willingness to learn Python.
• Proficiency in German and English.
• Experience in systematically analyzing extensive research literature, or strong willingness to learn.
• Experience in applying natural language processing methods to large datasets, or strong willingness to learn.
• Interest in addressing social science questions using computational methods (Computational Social Science)

Mansioni

• Systematic evaluation of research literature in social sciences, computational social science, and data science.
• Assistance in developing pipelines for automated detection of disinformation in large text corpora using machine learning models and LLMs.
• If necessary, assistance with the manual annotation of smaller datasets.

Conoscenze

Python

R

German language

English language

Literature review

NLP

Formazione

Bachelor/Master student

Strumenti

ML models

LLMs

Descrizione del lavoro

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 as soon as possible, our Department Computational Social Science (CSS), Team Transparent Social Analytics located inCologne, is looking for a Student Research Assistant (15,20 € / 16,09 € hourly rate, up to 10 hours per week, temporary). The departmentComputational Social Science (CSS) collects digital behavioral data and provides computer-based methods for collecting and analyzing such data for social science research. It also supports scientists with the integration of digital behavioral data into their research designs. The department's research focuses on the quality of digital behavioral data, the development and validation of computational social science methods and the transformation of digital societies. The BMFTR-funded project WIEGE (“Wiederholt Getäuscht” - “Repeatedly Deceived”) investigates how repeated, cross-platform political disinformation shapes young people’s everyday media experiences and what consequences it has for their attitudes, trust, and behavior. In the Transparent Social Analytics team, we are working on working packages within WIEGE that are concerned with the automated detection of disinformation in social media data. To this end, we compare various machine learning-based methods. We also use computational methods to analyze the content of cross-platform political disinformation.

Your tasks will be:

• Systematic evaluation of research literature in the fields of social sciences, computational social science, and data science
• Assistance in developing pipelines for the automated detection of disinformation in large text corpora using established machine learning models and LLMs
• If necessary, assistance with the manual annotation of smaller datasets

Your profile:

• Enrollment in a bachelor's (advanced) or master's program in sociology, political science, communication studies, linguistics, computer science, data science, or a related discipline
• Proficiency in Python, or proficiency in R with a willingness to learn Python
• Proficiency in German and English
• Experience in systematically analyzing extensive research literature, or a strong willingness to learn
• Experience in applying natural language processing methods to large datasets, or a strong willingness to learn
• Interest in addressing social science questions using computational methods (Computational Social Science)

Our Benefits:

• Exciting and practical insights into an interdisciplinary research project at the intersection of the social sciences and computer science
• An interdisciplinary work environment with a friendly and collegial atmosphere, as well as a wide range of opportunities to develop your professional and methodological skills, including the opportunity to write a thesis related to the project
• Flexible working hours and regulations for mobile working
• Very good conditions for reconciling work and family life
• Holistic company health management and discounted participation in the university's sports programme
• Promotion of your skills through further training measures

Contact

For further information concerning the tasks please contact Pia Schrot viaE-Mail. If you have questions about the application process, please contact Christine Laßmann viaE-Mail.

Interested?

Our reference number is: SHK-CSS-39