"Postdoc: Geospatial AI Modelling & Uncertainty Quantification of Carbon"

Job Summary: This postdoc position involves designing and implementing process-informed machine learning and uncertainty quantification methods for carbon turnover models. It focuses on fusing data science forecasting with process-based models to map soil and biomass carbon fluxes across Europe at high resolution. The role is part of the EU-funded Intergenerational Open Geospatial Carbon Registry (OGCR) project, aimed at quantifying and mapping carbon storage potential and policy scenarios.

Responsibilities:

• Designing and implementing process-informed machine learning and data augmentation for soil and biomass carbon forecasts and scenario modelling across Europe.
• Developing and benchmarking uncertainty quantification methods for space-time predictions and for spatial blocks.
• Developing visualisation prototypes to communicate uncertainty to end-users.
• Contributing to a computational framework for data production in cooperation with Research Software Engineers.
• Working closely with the workpackage team and collaborating with partners across Europe for data sharing, code exchange, and joint publications.

Qualifications and Requirements:

• Hold a PhD (or near completion) in statistics, applied mathematics, data science, environmental modelling, geosciences, or a related field with a strong quantitative focus.
• Deep understanding of statistical uncertainty quantification methods, sampling strategies, and error propagation techniques.
• Experience in spatial-temporal statistics, kriging methods, and handling autocorrelation.
• Interest in environmental biomass and soil mapping and modelling.
• Good programming skills in Python and/or R, with familiarity in reproducible coding and automated geospatial data analysis.
• Excellent scientific writing and communication skills in English.
• Willingness to collaborate in multidisciplinary teams and mentor students.
• Assets include prior experience in hybrid modelling, environmental science applications, interactive visualisation of uncertainty, and HPC or parallel computing.

What the Employer Offers:

• A position of 1.0 FTE for 30 months or 0.8 FTE for 37 months.
• Access to computational resources (HPC), GIS/data infrastructure, and datasets via collaborative networks.
• A supportive, interdisciplinary research environment within the Faculty of Geosciences, national research institutes, and EU consortia.
• Opportunities to lead subprojects, co-supervise MSc students, and build your academic profile.
• A gross monthly salary between €3,546 and €5,538 (salary scale 10 under the Collective Labour Agreement for Dutch Universities).
• 8% holiday pay and 8.3% year-end bonus.
• A pension scheme, partially paid parental leave, and flexible terms of employment.