Postdoctoral Researcher Geophysical Subsurface Imaging, AI, and Digital Twins

The University of Twente, Faculty ITC, wishes to increase the number of women in the faculty to have a more balanced staff profile. During all phases of the selection process, we will therefore prioritize selecting women who fit the profile.

Your challenge

Changing environmental conditions such as soil moisture, temperature, and subsurface heterogeneity strongly influence the quality of geophysical observations. Improving our ability to image and monitor the subsurface is essential for applications in infrastructure management, environmental monitoring, climate adaptation, and sustainable urban development.

You will develop and apply advanced methods for subsurface characterization by combining geophysical sensing, physical modelling, and artificial intelligence. You will:

• design and conduct research using geophysical techniques such as Ground Penetrating Radar (GPR), Electrical Resistivity Tomography (ERT), seismic, and electromagnetic methods;
• analyse and integrate geophysical datasets to characterize subsurface structures, buried infrastructure, and material properties;
• develop and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction;
• build physics-informed and hybrid AI models that combine geophysical knowledge with data-driven approaches;
• contribute to the development of dynamic digital twins for subsurface monitoring, forecasting, and decision support;
• collaborate with researchers and external stakeholders, publish results in leading journals, and present findings at international conferences.

The project offers the opportunity to work at the intersection of geophysics, AI, and digital twinning, contributing to next-generation technologies for understanding and managing the subsurface.

This position is embedded within the national Sector plan Earth and Environmental Sciences (AMW) programme and contributes to strategic research investments addressing climate resilience, environmental monitoring, and sustainable infrastructure management.

• A PhD in Geophysics, Applied Geophysics, Earth Sciences, Engineering Geology, Civil Engineering, Remote Sensing, or a related field.
• Experience with one or more geophysical sensing or imaging techniques (e.g. GPR, seismic methods, ERT, EM methods).
• Demonstrated experience in quantitative data analysis and scientific programming (e.g. Python, MATLAB, R, or similar).
• A strong publication record relative to career stage.
• Excellent communication and scientific writing skills in English.
• Ability to work independently while contributing to a collaborative and interdisciplinary team.
• An enthusiastic researcher who enjoys combining scientific innovation with practical applications.

The following experiences are a pré:

• Seismic imaging, inversion, migration, or advanced geophysical interpretation.
• Ground Penetrating Radar (GPR) applications and signal processing.
• Image and signal processing for geophysical datasets.
• Machine learning or deep learning applied to geoscience and subsurface characterization.
• Geological scenario modelling, uncertainty quantification, or predictive subsurface modelling.
• Data fusion and integration of multiple sensing techniques.
• Digital twins, environmental process modelling, or infrastructure monitoring applications.

The ideal candidate has a strong background in geophysical imaging and data analysis, combined with an interest in emerging AI methodologies. You are curious, collaborative, and motivated to develop innovative solutions for complex subsurface challenges. While the scientific core of the project lies in advancing geophysical imaging and interpretation, the outcomes are expected to contribute directly to climate-resilient infrastructure management and…