Working time: 65 % (25,35 hours/week).
Contract duration: The position is initially limited to 36 months.
Earliest start date: May 1, 2023
The successful candidate will develop and apply natural language processing (NLP) methods to analyze narratives on climate-related events, such as floods, droughts, heatwaves and storms. The goal is to identify which (i) narratives are predominant in media coverage and political discourse surrounding climate-related events, (ii) how they evolve over time and (iii) how they are linked to climate change adaptation. To this end, a text-as-data approach (using e.g. policy documents, newspapers, laws, and social media) will be applied. Prof. Christian Kuhlicke (University of Potsdam) will be the University supervisor, and Dr. Mariana Madruga de Brito will be the UFZ advisor. In order to meet the project aims, the PhD candidate will:
- Investigate how extreme events such as floods, droughts and heatwaves influence political and media narratives on the need to adapt to climate change
- Identify which societal actors (e.g. NGOs, government, industry) are linked to distinct narrative types
- Analyse the causal relationships between such disasters and changes in the discourse over time and across different regions (e.g. Germany, Europe)
- High-level publication of research results
- A vibrant research community in an open, diverse and international work environment
- Scientific excellence and extensive professional networking opportunities
- Excellent support and optimal subject-specific and general training with the UFZ HIGRADE graduate school
- Remuneration in accordance with the TVöD public-sector pay grade 13
- We support a good work-life balance with the possibility of part-time employment and flexible working hours
- Numerous company health management offerings
- An employer subsidy for the VVO job ticket
- PhD enrolment at the University of Potsdam
- Master’s degree in digital humanities, geography, computer social sciences or related discipline
- Programming and statistical competence (e.g. R or Python)
- Familiarity with machine learning, natural language processing is beneficial
- Proficiency in English
- Basic skills in handling and processing large datasets
- Motivation to work in an interdisciplinary environment, also in cooperation with modellers and natural scientists
Application Deadline: 13.02.2023
For more Information follow the link.