of University of Basel has announced a fully funded PhD position in hydrology focused on hydrological model and data interaction and machine learning applications for headwater catchment analysis. This position is offered within the Hydrogeology Research Group of the Faculty of Environmental Sciences and forms part of ANR-SNSF’s international research initiative FutureFlow.
The PhD program is expected to start in September 2026, or as agreed, and will be fully funded for four years.
Research: Understanding headwater catchments in a changing climate
Headwater catchments represent the most upstream parts of river systems and form an important part of Europe’s hydrological landscape. Despite its relatively small space footprint, it plays an important role in:
- Regulation of local water resources
- Maintenance of downstream river ecosystem
- Control of water availability during seasons and drought periods
- Mitigating climate change through groundwater storage systems
These systems are primarily governed by aquifers, which regulate both water storage and release to rivers.
However, headwater catchments remain poorly understood for the following reasons:
- Limited observation and monitoring data
- Complex interactions between geology, climate, and topography
- Difficulties in predicting hydrological behavior under changing climate conditions
The lack of reliable models constrains long-term water resource planning, especially in situations of increasing drought frequency and climate stress.
FutureFlow Project: Advances in Multi-Fidelity Hydrological Modeling
The PhD position is embedded in the FutureFlow project, an international effort to introduce software engineering concepts into hydrological modeling. This project focuses on:
- Multi-fidelity modeling approach
- Adaptive model selection and model switching
- A scalable framework for groundwater system simulation
- Improving predictions of hydrological responses under climate change
The overarching objective is to develop a flexible modeling system that allows models of varying complexity to be combined and adjusted to better represent groundwater and surface water interactions across European catchments.
Research goals and technical contributions of the doctoral program
The successful candidate will contribute to advances in data-driven hydrological modeling with a focus on machine learning and hybrid simulation frameworks.
Main research tasks include:
- Development of a multi-fidelity modeling approach for headwater systems
- Contributing to the HydroModPy modeling platform
- Applying machine learning techniques to estimate hydraulic properties across European catchments
- Evaluation of hydrological verification methods for characterizing watersheds
- Development of hybrid models to track and predict hydrological behavior in ungauged catchments.
- Using the climate storyline approach to assess vulnerability to extreme hydrometeorological events
This project is expected to improve both the predictive ability and conceptual understanding of groundwater and surface water interactions.
Scientific and practical implications
The research findings are designed to serve both the academic and applied communities by:
- Improving hydrological predictions under climate change scenarios
- Improve your understanding of groundwater and surface water coupling
- Supporting water resource management in drought-prone areas
- Advances in computational hydrology by integrating machine learning
This project will directly contribute to European-wide efforts in climate resilience and water security planning.
Candidate profile and required skills
Applicants are expected to have a strong academic background in the environmental and computing fields.
Required qualifications
- Master’s degree in hydrology, hydrogeology, data science, computer science, or related field
- Strong interest in environmental data analysis and numerical modeling
- Python programming proficiency
- Excellent written and spoken English skills
desirable attributes
- Interest in science communication and interdisciplinary research
- Experience with hydrological or environmental modeling systems.
- Knowledge of machine learning or data-driven modeling approaches
This role requires strong abilities for independent research and collaboration within international teams.
Research environment and institutional collaboration
The PhD candidate will participate in a large European research consortium including:
- University of Basel
- University of Neuchâtel
- University of Rennes 1
- CNRS
- BRGM
- ENS Paris
- Ewag
- Utrecht University (research stay)
Selected candidates will be part of a cohort consisting of:
- 4 postdoctoral researchers
- 2 research engineers
- 7 principal researchers
Supervision is provided by:
- Professor Oliver S. Schilling (University of Basel)
- Professor Clément Roque (University of Neuchâtel, co-supervisor)
Training, mobility and research opportunities
This position is located within the Ministry of Environment and Science in Basel, Switzerland. This includes access to advanced research infrastructure, technical support, and integration into:
- Graduate School of Environmental Sciences
- Water and Earth Systems PhD Program in Switzerland
Other research mobility opportunities include:
- 3 month research stay at Utrecht University
- 3 months research stay at BRGM (French Geological Survey)
These placements are designed to enhance interdisciplinary collaboration and applied research experiences.
Application process and required documents
Applications must be submitted online via the University of Basel application platform. The required documents are:
- 1 page motivation letter
- Resume (CV)
- Copy of master’s degree diploma
- Contact details of at least two reviewers
- Optional: Description of previous research projects, including objectives, results, and personal contributions (up to half a page)
Applications will be reviewed on a rolling basis until the position is filled.
Contact and deadline information
For further inquiries, applicants should contact the following:
Professor, Dr. Oliver S. Schilling
Email: [email protected]
This position will begin in September 2026 or, by agreement, no later than January 2027.
conclusion
The PhD opportunity at the University of Basel represents a highly interdisciplinary research position at the intersection of hydrology, machine learning and computational modeling. This project aims to improve the understanding and prediction of headwater catchment systems under increasing climate pressures by integrating advanced data-driven approaches with hydrological science.
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Disclaimer: Global South Opportunities (GSO) is not the organization providing this opportunity. For inquiries, please contact the official organization directly. Please do not submit your application or resume to GSO as it cannot be processed by GSO. Due to the large volume of emails we receive every day, we may not be able to reply to all inquiries. Thank you for your understanding.
