PhD Student MiningBrines DCPore-scale reactive transport modelling utilization of g

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The Paul Scherrer Institute PSI is the largest research institute for natural and engineering sciences within Switzerland. We perform cutting-edge research in the fields of future technologies, energy and climate, health innovation and fundamentals of nature. By performing fundamental and applied research, we work on sustainable solutions for major challenges facing society, science and economy. PSI is committed to the training of future generations.

Therefore, about one quarter of our staff are post-docs, post-graduates or apprentices. Altogether, PSI employs 2300 people.

For many years the Laboratory for Waste Management has conducted multi-disciplinary research on safety and design of geological repositories for radioactive waste and flows relevant to nuclear reactor technologies using a unique combination of experimental infrastructure and modelling capabilities.

For a Marie Skłodowska-Curie Doctoral Network (MSCA-DN) project we are looking for a PhD Student for Mining Brines DC16:
Pore-scale reactive transport modelling for utilization of geothermal reservoirs. 03.03.2026

• Doctoral
• 100%

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The project “Reactive transport modeling (Hydraulic Chemical) at the pore scale and upscaling to reservoir scale” develops advanced pore scale reactive transport modeling capabilities by extending an in house lattice Boltzmann based transport solver to explicitly resolve microstructural evolution in reservoir rocks driven by mineral dissolution and precipitation. These simulations quantify how coupled flow, transport and chemistry processes cause dynamic changes in pore geometry, in transport properties, and reactive surface area under geothermal conditions.

Building on these high resolution models, the project establishes robust upscaling strategies to transfer pore scale process understanding to geothermal reservoir scale reactive transport formulations, while preserving key mechanistic controls.

To improve computational performance and multiphysics couplings, the work integrates AI/ML methods (e.g. neural networks, neural operators) to accelerate both pore scale simulations and the associated upscaling workflows, enabling realistic simulations, efficient parameter exploration and reduced order model generation.

• Implement Lattice Boltzmann (LB) solver for modelling processes at pore scale in 2D/3D realistic multimineral pore structures (synthetic and tomography driven)
• Develop surrogate models to accelerate simulation of chemistry and couple with LB
• Quantify the impact of reactions and microstructural evolution on permeability and transport properties relevant to resource extraction, and derive mechanistic correlations for upscaling
• Integrate AI/ML-assisted sensitivity analysis and uncertainty quantification to evaluate prediction reliability and account for input data variability.

You will be enrolled at the University of Bern and receive your PhD title from University of Bern. This position is part of the Marie Sklodowska Curie Action (MSCA) Doctoral Network (DN) “Mining Brines” (Multidisciplinary Integration and Networking for Increased sustainability and multi-resources valorization of Geothermal BRINES. You will have the status as a “SERI-funded MSCA DN Grantee”. As part of the MSCA DN, you will visit the Instituto Nazionale die Geofisica e Vulcanologia, Osservatorio Vesuviano (INGV) in Naples, Italy, the Geological and Mining Bureau (BRGM) in Orléans, France, the GFZ Helmholtz-Zentrum für Geoforschung in Potsdam, Germany and Collaboration Betters the World (CBTW) in Germany for ca.

2 months each. You will collaborate closely with the other Mining Brines research projects and participate in network training and workshops.

• Master’s degree (or equivalent) in a relevant discipline
• Strong motivation for interdisciplinary research
• Excellent command of spoken and written English (mandatory)

• Programming skills (e.g. python or
  
  C). Familiarity with machine learning techniques is a plus
• Background in porous media flows or CFD. Experience with the lattice Boltzmann would…