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Project assistant computational social sciences

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Lund University

Lund University was founded in 1666 and is repeatedly ranked among the world’s top universities. The University has around 46 000 students and 8 500 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

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 ( [email protected] ) 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.

The Faculty of Social Sciences at Lund University is one of the leading education and research institutions in Sweden and operates both in Lund and Helsingborg.

The Faculty of Social Sciences at Lund University is one of the leading education and research institutions in Sweden and operates both in Lund and Helsingborg.

The Department of Human Geography (Institutionen för kulturgeografi och ekonomisk geografi) at Lund University is a research-intensive academic unit within the Faculty of Social Sciences. It combines long academic traditions with contemporary and highly internationalised research and education.



The department hosts a broad portfolio of education at undergraduate, master’s and doctoral levels, including internationally oriented programmes such as the Master’s in Human Geography.

The department comprises a diverse faculty. The exact staffing varies, but the department currently employs 55–60 academic and administrative staff. The department educates roughly 400 full-time students across bachelor’s and master’s programmes, and it employs about 15 doctoral students.

The research environment is strongly oriented towards external funding and has been successful competitively at national and European levels. The department’s research and education activities have received very favourable assessments in internal and external evaluations, positioning it among Lund University’s leading disciplinary domains.

Lund University as a whole performs prominently in global rankings. According to the most recent QS World University Rankings, Lund University is placed #72 globally and achieves strong subject-level positions, including in fields related to human geography and environmental sciences. Lund University also ranks #1 in the world for sustainability in the same ranking, reflecting its strengths in socially and environmentally relevant research and education.

We kindly decline all sales and marketing contacts.

Type of employment Special fixed-term employment Employment expires 2027-10-30 Contract type Part-time First day of employment 2026-11-01 Salary Månadslön Number of positions 1 Full-time equivalent 65% City Lund County Skåne län Country Sweden Reference number PA2026/2451 Contact

- Jonathan Friedrich, +462226832, [email protected]
- Elin Johansson, 046222000, [email protected]

Union representative
- SEKO: Seko Civil, (phone hidden), [email protected]
- OFR/ST:Fackförbundet ST:s kansli, (phone hidden), [email protected]
- SACO:Saco-s-rådet vid Lunds universitet, (phone hidden), [email protected]

Published 31.Aug.2026 Last application date 21.Sep.2026

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Project assistant computational social sciences

Login and apply

Lund University

Lund University was founded in 1666 and is repeatedly ranked among the world’s top universities. The University has around 46 000 students and 8 500 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

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.

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 ( [email protected] ) 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.

The Faculty of Social Sciences at Lund University is one of the leading education and research institutions in Sweden and operates both in Lund and Helsingborg.

The Faculty of Social Sciences at Lund University is one of the leading education and research institutions in Sweden and operates both in Lund and Helsingborg.

The Department of Human Geography (Institutionen för kulturgeografi och ekonomisk geografi) at Lund University is a research-intensive academic unit within the Faculty of Social Sciences. It combines long academic traditions with modern and highly internationalised research and education. The department hosts a broad portfolio of education at undergraduate, master’s and doctoral levels, including internationally oriented programmes such as the Master’s in Human Geography.

The department comprises a diverse faculty. The exact staffing varies, but the department currently employs 55–60 academic and administrative staff. The department educates roughly 400 full-time students across bachelor’s and master’s programmes, and it employs about 15 doctoral students.

The research environment is strongly oriented towards external funding and has been successful competitively at national and European levels. The department’s research and education activities have received very favourable assessments in internal and external evaluations, positioning it among Lund University’s leading disciplinary domains.

Lund University as a whole performs prominently in global rankings. According to the most recent QS World University Rankings, Lund University is placed #72 globally and achieves strong subject-level positions, including in fields related to human geography and environmental sciences. Lund University also ranks #1 in the world for sustainability in the same ranking, reflecting its strengths in socially and environmentally relevant research and education.

We kindly decline all sales and marketing contacts.

Type of employment Special fixed-term employment Employment expires 2027-10-30 Contract type Part-time First day of employment 2026-11-01 Salary Månadslön Number of positions 1 Full-time equivalent 65% City Lund County Skåne län Country Sweden Reference number PA2026/2451 Contact

- Jonathan Friedrich, +462226832, [email protected]
- Elin Johansson, 046222000, [email protected]

Union representative
- SEKO: Seko Civil, (phone hidden), [email protected]
- OFR/ST:Fackförbundet ST:s kansli, (phone hidden), [email protected]
- SACO:Saco-s-rådet vid Lunds universitet, (phone hidden), [email protected]

Published 31.Aug.2026 Last application date 21.Sep.2026

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📌 Project assistant computational social sciences/2451) (Dharavi)
🏢 Sustainable Urban Design (SUDes) Programme
📍 Dharavi