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”.

Reference Number 10769

Our section is working on understanding the dynamical evolution of the hazardous space radiation environment and developing tools for the prediction of the adverse effects of the space environment utilising satellite observations, physics-based numerical models, machine learning, and data assimilation. Our research will help safely design and operate satellites and maintain ground networks. We try to bridge our theoretical studies with high-performance tools that can be used in science, predictions, and applications.

Your responsibilities:

• Maintain structured repositories for scientific data and software, ensuring version control, accessibility, and reproducibility
• Manage and further develop the section’s project websites, including integration of interactive tools and real-time visualisations for space weather data
• Design and implement software pipelines for processing, analysing, and visualising satellite data (e.g. GOES, POES, ARASE)
• Adapt and extend existing scientific codes and models for application to new space physics problems
• Contribute to the development and integration of numerical models (e.g. VERB) and machine learning frameworks (e.g. KpML, PINE, NET)
• Perform analysis of observational and model data from the near-Earth space environment, contributing to scientific publications and presentations
• Architect computational workflows ensuring robust, reproducible, modern and efficient research processes
• Support technical team activities, including interviews, and mentoring
• Collaborate with international research partners and contribute to over all scientific development

Your qualifications:

• A Master's degree in computer sciences or natural sciences
• Knowledge of data engineering and data science concepts
• Several years of working experience with IT programming or scientific programming
• Knowledge of Unix operating systems and maintenance of Unix Workstations
• Experience with various programming languages, including C++, Python and Matlab
• Ability to work with large datasets
• Experience with machine learning, data mining and data assimilation is a plus
• Knowledge of git, docker, kubernetes, and/ or metadata is a plus
• Ability to work in a collaborative and multi-cultural environment
• Attention to detail and strong organisational skills
• Excellent interpersonal and communication skills

What we offer:

• Ambitious and varied tasks in a dynamic and international research environment
• State-of-the-art equipment
• Public service benefits
• Extensive training opportunities
• Professional career advice offered by our in-house Career-Centre
• Flexible working hours and conditions
• Support with finding a good work-life balance offered by benefit@work
• Institute day-care centre on site
• Working at the Albert Einstein Science Park on the Telegrafenberg in Potsdam
• Workplace within walking distance of Potsdam main train station, or just a short ride on the shuttle bus