PhD Student for Mining Brines DC13: Modelling the Evolution of Geothermal Waters during Multi-Resource Extraction / PhD Student for Mining Brines DC13: Modelling the Evolution of Geothermal Waters during Multi-Resource Extraction

Your Tasks

The project - Modeling workflow development and application for fluid chemistry evolution from extraction to re-injection - aims to advance the understanding and prediction of fluid behavior in complex geo-energy systems from extraction to reinjection. A central objective is to quantify how geological, geochemical, and engineering factors jointly influence fluid composition and, ultimately, the efficiency of geothermal energy production alongside the extraction of critical minerals.

To achieve this, a batch-type geochemical modeling workflow will be developed using open-source tools (e.g., Marimo, Jupyter) that allow the calculation of chemical processes (e.g., precipitation/dissolution of minerals) during the transport and processing of geothermal fluids with the PSI GEMS thermodynamic solver. More complex coupled reactive transport processes, such as scaling of pipes, will be imported from separate sub-models or as surrogate models. The workflow will enable robust modeling of reactive fluids, phase behavior, and coupled process interactions during heat extraction combined with microbial, physical, or chemical extraction of critical materials like lithium. Once established, the workflow will be tested and refined through case studies provided by industrial partners, ensuring its direct relevance to real-world challenges and facilitating technology transfer.

Machine learning-based sensitivity analysis will be incorporated to identify the parameters that most strongly influence model outcomes. This component will help quantify uncertainty, highlight key leverage points for operational decision-making, and evaluate the robustness of predictions under varying operational conditions.

Expected Outcomes

• Develop an easy-to-use computational workflow based on open-source software and the GEMS3K Gibbs-Energy Minimization (GEM) thermodynamic solver.
• Set up a thermodynamic model (fluid model, thermodynamic database) that can be utilized in PSI GEM software to model critical raw materials (CRMs) and heat extraction.
• Implement interfaces to results/models from other projects (e.g., Thermo-Hydro-Mechanic (WP2, WP3), Thermo-Hydro-Chemical (WP3), or Biological (WP4) processes) to understand their influence on CRMs and heat extraction.
• Conduct a machine learning-based sensitivity analysis to identify influential parameters and evaluate prediction robustness.
• Test and apply the workflow to case studies from industrial partners.

Your Profile

Required Qualifications

• Master’s degree in geosciences (such as geochemistry, geology, geophysics, or a related discipline) with a solid knowledge of (geo)chemistry, or alternatively, a master’s degree in chemistry, chemical engineering, or a related discipline with a strong interest in geoscience applications.
• Strong motivation for interdisciplinary research.
• Excellent command of spoken and written English (mandatory).

Desirable Skills

• Familiarity with thermodynamic and/or (geo-)chemical software.
• Experience with programming or scripting languages (e.g., Python, R, Matlab, etc.).

We Offer

PSI: Our institution is based on interdisciplinary, innovative, and dynamic collaboration. You will benefit from systematic on-the-job training, personal development opportunities, and a strong vocational training culture. If you wish to optimally combine work and family life or other personal interests, we offer modern employment conditions and on-site infrastructure to support this balance.

MiningBrines: An international network of 32 academic and industrial partners across multiple disciplines offers an innovative doctoral training program addressing Europe's strategic need for sustainable access to critical raw materials, energy gases, and renewable energies. You will benefit from interdisciplinary training in geosciences, biogeochemistry, artificial intelligence, and socio-economic analysis. The position is funded for 36 months with a competitive salary, allowances, and additional funding for technical training and conference participation.

Interested candidates are invited to apply online using the form below. Only applications matching the job profile will be considered.

Contact Information

For further information, please contact Dr. Georg Kosakowski at georg.kosakowski@psi.ch.

Paul Scherrer Institute, Human Resources Management, Serdal Varol, 5232 Villigen PSI, Switzerland.