Benchmarking Seismic Source Models for Geothermal Operations. We are seeking a highly motivated Postdoctoral Researcher who will work on two closely related research projects addressing subsurface challenges in geothermal energy production and CO₂ storage. The role focuses on developing, implementing, and benchmarking advanced numerical models to understand and manage induced seismicity, fault reactivation, and near-wellbore processes such as salt precipitation and hydrate formation. The work integrates processes across scales, from near-wellbore physics to reservoir- and fault-scale behaviour, supporting the development of robust, physics-based modelling tools for subsurface energy applications.
Responsibilities- Design and implement benchmark scenarios for (shear) stress modelling along faults and seismic modelling in geothermal operations, supporting fault stressing and seismicity analyses.
- Establish validated reference scenarios for this benchmark with varying levels of complexity, including cases with analytical or semi-analytical ground truths.
- Develop accurate near-wellbore physical models for salt precipitation and hydrate formation during CO₂ injection, explicitly accounting for impurities in the CO₂ stream.
- Bridge near-wellbore, reservoir, and fault-scale processes through consistent numerical modelling and upscaling.
- Support model evaluation, comparison, and performance assessment across both projects, in close collaboration with internal and external stakeholders.
- Background in geophysics, reservoir engineering, geomechanics, or a related field.
- Strong background in numerical modelling of subsurface processes, including fluid flow, geomechanics, or coupled multiphysics systems.
- Experience with seismic source modelling, induced seismicity, or fault mechanics.
- Familiarity with analytical and numerical modelling approaches.
- Ability to work with complex geological and reservoir datasets.
- Strong documentation and communication skills.
- Experience working in collaborative, research-driven projects is an asset.
- Experience with geothermal systems or subsurface energy applications.
- Experience with near-wellbore modelling, including completions, perforations, and damage zones.
- Knowledge of benchmark model development and model validation workflows.
- Ability to translate scientific concepts into practical modelling scenarios.
TU Delft (Delft University of Technology)
Delft University of Technology is a leading international university combining science, engineering and design. It values diversity and openness and invites you to apply. Your application will receive fair consideration.
Conditions of employment- Duration of contract: 24 months. Temporary position.
- Job: 36-38 hours per week.
- Salary and benefits follow the Collective Labour Agreement for Dutch Universities.
- Excellent pension scheme via ABP; option to assemble an individual employment package each year.
- Flexible working week; leave: 232 hours per year (38-hour week). Leave can be bought or sold via the individual budget.
- Opportunities for education, training and courses; partially paid parental leave.
- Vitality program supports healthy and energetic working.
Relocation support is available. The HR unit provides information on relocation and integrates a Dual Career Programme to assist accompanying partners.
Additional informationFor more information about this vacancy, please contact Denis Voskov at d.v.voskov@tudelft.nl.
Application procedureApply via the online application button and upload a recent CV and motivation letter explaining how your experience matches the requirements (max 2 pages) no later than 17 February 2026.
- Publication list including a one-page summary of your PhD thesis.
- Contact details for two referees.
You can address your application to Denis Voskov.
Please note:
- You can apply online. Applications sent by email or post will not be processed.
- As part of knowledge security, TU Delft conducts a risk assessment during recruitment. The assessment may influence the final stages of the selection process. Personal data processing is on GDPR basis (public task in the public interest). More information about knowledge security is available on the TU Delft website.
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