The Department of Physical geography is looking for a highly motivated PhD candidate with a background in hydrology, earth system science, atmospheric science, agroecology or other appropriate fields. You will work on the project “Physics-informed AI-modelling of land surface processes in a global hydrological model” as part of a large international project to improve the modelling of global water resources.
Your job
In many areas of the world, water resources are overexploited, leading to the depletion of water volumes and deterioration of water quality in aquifers, reservoirs and rivers. This, in turn, leads to a greater pressure on the remaining water resources and more water scarcity in different sectors. At the department of Physical Geography at Utrecht University, we have developed the global hydrology and water resources model PCR-GLOBWB
to analyse these global water challenges.
As a PhD you will improve the land surface representation of PCR-GLOBWB by including new to be developed soil and vegetation modules and an energy balance. Secondly you will use AI-based surrogates to speed up calculations and allow for better calibration of the land-surface modules to observations. Finally, you will work on improving the drought response of the vegetation in PCR-GLOBWB. Throughout the process model improvements will be compared to local and remotely sensed observations during extensive validation and sensitivity analysis.
A personalised training programme will be set up, reflecting your training needs and career objectives. About 20% of your time will be dedicated to this training component, which includes training on the job in assisting in the Bachelor and Master programmes of the department at Utrecht University.
Your qualities
We welcome a motivated team-player who recognizes themselves in the following description:
You have completed an MSc degree in hydrology, earth system science, computer science, atmospheric science, agroecology or a related discipline by the time the position starts.
Preferably, you will also have:
- Interest in global water issues and earth system modelling;
- Strong quantitative methodological skills, for instance knowledge of (spatial) data analysis, hydrological modelling, AI-based methods;
- Experience with programming languages (e.g. Python);
- Motivation to cooperate in a diverse and multidisciplinary research team;
- Strong social and communication skills.
Due to the international character of our research, good command of spoken and written English is essential. We highly encourage applicants from all members of our community and of diverse backgrounds to join us.
