The Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences is the national centre for research into the geosphere. With around 1,650 employees, we develop a sound understanding of systems and processes of the solid Earth as well as strategies and options for action to counter global change, understand natural hazards and sustainably secure energy and raw material requirements.

The Section Hydrology at the GFZ searches for a PhD candidate to work in the Helmholtz funded project “EXTREME-ADAPT - Quantifying the effect of adaptation measures on spatiotemporal changes in flood and drought risk”. The work will be led by Dr. Heidi Kreibich, Section Hydrology, German Research Center for Geosciences, Potsdam. 

We seek a PhD candidate with experience in machine learning, statistics and programming and with interest in hydrological extremes and risk research. The PhD candidate is expected to analyse timeseries of flood and drought losses and their potential drivers with a focus on establishing an automatic analyses process.  

The successful candidate should have the interest and ability to participate in collaborative and interdisciplinary research activities and discussions in the field of adaptation and risk of hydrological extremes. The candidate is also expected to closely collaborate with partners from other Helmholtz Centres, and present, publish and communicate research results at scientific meetings and in scholarly journals.

Your responsibilities:

• Analyse flood and drought impact data using data-driven approaches
• Establish (semi-)automatic processes for analysing flood and drought impacts including writing well-documented, reusable code (Python or R)
• Collaborate closely with project partners in an interdisciplinary context 
• Present, publish and communicate research results at scientific meetings and in scholarly journals
• Undertake a PhD study (e.g. https://www.geographie.hu-berlin.de/de/institut/promotionen_habilitationen/promotionen, at HU-Berlin)
• Deliver according to the project timelines and university/department requirements 

Your qualifications:

• Master's degree in Environmental Sciences, Engineering, Geoinformatics or related fields
• Programming skills (Python, R)
• Expertise in machine learning, Bayesian statistics is beneficial
• Capacity for interdisciplinary teamwork and excellent communication skills
• Ability to communicate in English fluently (German language command is helpful but not mandatory)