PhD Researcher (f / m / x) in In4Nile PhD-Cohort : Monitoring water quality impacts using NLP and LLMs (f / m / x)

The UFZ

The Helmholtz Centre for Environmental Research (UFZ) with its 1,100 employees has gained an excellent reputation as an international competence centre for environmental sciences. We are part of the largest scientific organisation in Germany, the Helmholtz association. Our mission : Our research seeks to find a balance between social development and the long-term protection of our natural resources.

The job

In the PhD cohort “In4Nile” - Advancing Water Quality Information in the Nile River Basin , we offer four PhD Positions. In4NILE addresses the limited availability of water quality information in the Nile basin by developing and applying low-cost sampling techniques, mining of existing open (geo)datasets, exploring the use of unstructured data sources through natural language processing, and by developing basin-scale, multi-pollutant spatially explicit water quality models. Building on this framework, the PhD candidate (f / m / x) will leverage the increasing amount of unstructured text data and advances in natural language processing (NLP), large language models (LLMs), and machine learning to extract, analyze, and spatialize pollution-related knowledge. Traditional monitoring approaches, which rely on sparse in situ measurements, offer only a partial view of how citizens and stakeholders perceive the impacts of pollution. In contrast, text sources such as news and institutional documents provide information on how pollution is experienced, debated, and understood by local communities.

Your tasks

• Conduct an AI-assisted systematic review of pollutants in the Nile Basin using multilingual scientific databases.
• Use text classification and LLM-driven information extraction to identify pollutants, their sources, and the locations of affected areas across scientific literature, reports, and media news.
• Compare public and institutional narratives with scientific evidence and biophysical data on water pollution.
• Develop a Nile Basin knowledge-retrieval chatbot to deliver referenced, uncertainty-aware answers.
• Communicate results through scientific publications, presentations, and collaborative work within an interdisciplinary team of the In4Nile cohort.

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