GFZ is Germany's national centre for solid Earth research. We advance the understanding of dynamic processes to address global challenges, from mitigating the impacts of natural hazards and sustaining our habitat amid global change to responsibly managing georesources. We are part of the Helmholtz Association, the largest German scientific organisation. With around 1,200 employees as well as ca. 500 guest researchers, we contribute to the Helmholtz Research Field Earth and Environment, aligning cutting-edge research with societal relevance and international collaboration. Our work integrates multidisciplinary studies across Earth's system components, leveraging advanced technologies and infrastructure to research solutions and to transfer our knowledge to society. We are doing this according to our vision: “Taking the pulse of our Earth to safeguard a habitable planet”.

Computer models of reactive transport play a crucial role in addressing major environmental and societal challenges. These include safety assessments for radioactive waste disposal, groundwater contamination remediation, and geothermal resource development. 

If you want to do research with a purpose and want to contribute to the analysis and evaluation of uncertainties in reactive transport simulations, this position is for you. In your role, you will work with established methods of uncertainty analysis as well as innovative approaches using machine learning and artificial intelligence. 

If you have a strong quantitative background such as data science, statistics or computer science and are eager to apply these skills to environmental research, we encourage you to apply. Additional knowledge in geosciences is an advantage but not a requirement.

Your responsibilities:

• Use geochemical and coupled reactive transport models to tackle key scientific questions
• Enhance existing numerical models and apply statistical methods for local and global sensitivity analyses, including machine learning-based emulators and surrogate models
• Quantify and analyze uncertainties in geochemically complex natural systems
• Design and evaluate different scenario analyses to improve predictions and reliability of simulations
• Present your research findings at national and international conferences and publish in leading scientific journals. We support professional growth and visibility within the research community.
• Provide scientific and technical support for ongoing research projects within your area of expertise
• Engage in academic activities such as contributing to courses at the Institute of Geosciences within the doctoral curriculum of the University of Potsdam. We encourage collaborative teaching experiences and collaboration across different disciplines and cultures.

Your qualifications:

• A Master’s degree in computer science, statistics, applied mathematics, geosciences, or a related field
• Strong programming skills in R, Python, or Julia are required; knowledge of C/C++ is an advantage
• Experience in machine learning, data analysis, and/or numerical modelling is highly valued
• Familiarity with hydrogeochemistry, mass transport modelling, or hydrogeology is a plus
• Interest in applying numerical simulation programs to tackle scientific challenges
• Enjoy working in interdisciplinary and international teams where collaboration and new perspectives are valued