We are searching for a PostDoc candidate to improve the usability of large climate data sets. The project will help to make future climate ensemble simulations more efficient by removing redundant information in a physically consistent way. The Earth System Modelling Section at GFZ is responsible for the development of numerical models of large-scale mass transport processes in the Earth’s geosphere. The successful candidate is expected to perform a wide range of numerical simulations as well as physically constrained data science and data analysis tasks.

Your responsibilities:

• Develop physics based nonlinear aggregation of large climate model ensemble data
• Design, execute, and evaluate scenarios to establish the limits of the aggregation method
• Improve the robustness and usability of the aggregation method
• Statistical analysis of residuals and forecast errors arising from deficits in the aggregation method and its application
• Collaborative work in a highly interdisciplinary and international team
• Presentation of your results at international conferences and project meetings
• Publication of your results in international scientific journals

Your qualifications:

• Master`s degree or equivalent and PhD degree in physics, meteorology, geosciences, or a related field
• Strong skills in scientific programming with Python or R and Fortran
• Experience with numerical Earth system models
• Good command of English language