The Faculty of Natural and Environmental Sciences (iES Landau), Institute for Environmental Sciences at RPTU Kaiserslautern-Landau (Campus Landau), is currently seeking a Postdoctoral Researcher in Artificial Intelligence for Chemical Risk Prediction.

Description

The position will be part of a team evaluating the presence and ecological effects of environmental chemicals on large spatio-temporal scales. We apply meta-analysis, geostatistics, graph databases, modeling, machine learning and semantic web technologies to analyse and link these data. We furthermore aim to present the results using innovative and appealing web approaches. The position is part of the Carl-Zeiss project “AI4ChemRisk” (AI for Chemical Risk Prediction in Aquatic Environments) collaborating with leading research groups in AI, Machine-Learning and Environmental Data Science at the RPTU and abroad.

Your area of ​​responsibility:

• Integration of chemical data using ontologies
• Prediction of molecular properties
• Interactive visualization tools
• Large language models for natural language interaction
• Stakeholder engagement, outreach, and collaboration

Your requirements profile:

Successful candidates will hold a diploma or MSc and a PhD in a topic relevant to (data-driven) Ecotoxicology or Environmental Informatics. We prefer experience in data science, specifically in the representation of complex spatio-temporal environmental or ecological data. However, other contributions to our main tasks are also considered.

We offer:

• E13 TV-L full-time (39h/week), up to 6 years, starting 01.05.2026 in beautiful Landau
• Work in a motivated, innovative team focusing on data-driven ecotoxicology
• Integration into various ecotoxicological research tasks of national and global scopes
• Flat hierarchies
• Flexible hours/home office, family support, job ticket and of course all Palatinate Forest perks.​

Application

We look forward to receiving your detailed application (CV, references, etc.) by 25.03.2026 at the latest.

Please submit your application using the “Online Bewerbung” via our application portal (https://jobs.rptu.de).

More information about the position: https://jobs.rptu.de/jobposting/9b691f29381eb2342b841cfec9361f368fc62ca0

For further questions, please contact Prof. Dr. Ralf Schulz (E-mail: r.schulz@rptu.de).