Project assistant computational social sciences

Requirement profile

The project assistant will be employed in the project “Leveraging large-scale newspaper data to uncover regional valuations of the green transition in the European Union” funded by Crafoord foundation. This project examines how the green transition is perceived, valued, and contested across different regions in three European countries (Sweden, Denmark, Germany), using a novel machine learning approach combining NLP and LLMs to analyse newspaper data. Findings will inform place-based, just governance approaches and advance NLP-based methods in social science research.

The project assistant is expected to

• Conduct research on the green transition in Europe in different geographies (Sweden, Denmark, Germany) in collaboration with the project team using computational methods;
• Work closely together with the project team and contribute to joint activities;
• Assist in writing scientific publications during the employment.
  
  

Qualifications

Requirements for the job are:

• Strong interest in academic research and societal transformations
• Curiosity for interdisciplinary research approaches at the intersection of human geography and computational methods
• Master's degree in a relevant field (e.g., Computational Social Science, Data Science, Computer Science, Statistics, Information Science, Digital Humanities, Economics, Political Science, or related disciplines) with strong quantitative and computational training.
• Experience with data management and data processing; ideally working with large-scale textual datasets and managing computational workflows for text mining and analysis
• Experience with natural language processing (NLP) techniques, including some of the following: Topic modelling, Named entity recognition (NER), Sentiment analysis and opinion mining, Text classification and clustering
• Experience or interested in learning how to use large language models (LLMs) for information extraction, semantic annotation, clustering, classification, summarization, or other large-scale text analysis tasks.
• Proficiency in spoken and written English

Desirable for the job is:

• Proficiency in Python for data processing, text analysis, and reproducible research workflows.
• Experience with multilingual text analysis, particularly Swedish, Danish, and German languages.
• Experience working with newspaper, media, or other large-scale historical text corpora.
• Proficiency in Danish, German, and Swedish
  
  

Employment
The employment is a fixed-term employment for one year at 65% with a desired start date on 01/10/2026 or as agreed.

Contact Jonathan Friedrich (jonathan.friedrich@keg.lu.se) for questions regarding the application.

Application
You application should contain the following:

Cover Letter (max. 1 page): Outline your motivation and fit for the position. Curriculum Vitae (CV): Include links demonstrating relevant skills (e.g., GitHub, portfolio). Academic Work Sample: Provide an independently written work (e.g., Master’s thesis, or work in progress). 

The university applies individual salary setting. Please feel free to state your salary expectations in your application.