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Phd researcher (f/m/x) in in4nile phd-cohort: monitoring water quality impacts using nlp and llms (f

Leipzig
Helmholtz Centre for Environmental Research - UFZ
Inserat online seit: 7 Dezember
Beschreibung

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

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.
Place of work

Leipzig Working time

65 % (25,35 h / week) Contract limitations

limited contract / 36 months Salary

Remuneration according to the TVöD public-sector up to pay grade 13 including attractive public-sector social security benefits. Contact

Your contact for any questions you may have about the job:
Tais Maria Nunes Carvalho (tais-maria.nunes-carvalho@ufz.de)
Mariana Madruga de Brito (mariana.brito@ufz.de)

Your application

Please submit your application via our online portal with your cover letter, CV (please omit your photo, age, or marital status) and relevant attachments.
Diversity and Inclusion

The UFZ has a strong commitment to diversity and actively supports equal opportunities for all employees regardless of their origin, religion, ideology, disability, age or sexual identity.
We look forward to applications from people who are open-minded and enjoy working in diverse teams.

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.
We offer

* Excellent supervision and optimal professional and interdisciplinary qualification through our HIGRADE graduate programme
* The freedom to master even the most demanding challenges between basic research and practical application
* The opportunity to work in interdisciplinary, international teams and benefit from a wide range of perspectives
* Firstclass integration into national and international research networks to work together on global challenges
* Excellent research infrastructure and research data management to optimally support your work
* A wide range of options for balancing care responsibilities and work through our family office
* Competent support and advice for international colleagues arriving at the UFZ from the 'International Office'
* Special annual payment, capital-forming benefits and subsidised Deutschland-Job-Ticket
* A workplace in a vibrant region with a high life quality and social and cultural diversity
Your profile

* Master's degree (or equivalent) in geography, computational social sciences, digital humanities, computer sciences, environmental sciences, environmental engineering, water resources, or related fields.
* Good command of scientific programming (e.g., Python or R) Experience in handling large datasets is an advantage.
* Interest in natural language processing, text mining, and machine learning.
* Interest in the societal consequences of water pollution.
* Ability to work independently and collaboratively within an interdisciplinary research environment.
* Good command of written and spoken English.
Apply now
Application deadline: 12.01.2026

More information about jobs at the UFZ:

LinkedIn @UFZ

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