PhD Student for MiningBrines DC13: Modelling the evolution of geothermal waters during multi-resource extraction
PhD Student for MiningBrines DC13: Modelling the evolution of geothermal waters during multi-resource extraction
PhD Student for MiningBrines DC13: Modelling the evolution of geothermal waters during multi-resource extraction
PhD Student for MiningBrines DC13: Modelling the evolution of geothermal waters during multi-resource extraction
Paul Scherrer Institute
Forschung
Villigen
- Art der Beschäftigung: Vollzeit
- Vor Ort
- Zu den Ersten gehören
PhD Student for MiningBrines DC13: Modelling the evolution of geothermal waters during multi-resource extraction
Über diesen Job
PhD Student for MiningBrines 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 re-injection. A central objective is to quantify how geological, geochemical, and engineering factors jointly influence fluid composition and, ultimately, the efficiency of geothermal energy production together with extraction of critical minerals.
To achieve this, a batch type geochemical modelling workflow will be developed using open source tools (e.g. marimo, jupyter) that allows to calculate chemical processes (e.g. precipitation/dissolution of minerals) during transport and processing of geothermal fluids with the PSI GEMS thermodynamic solver. More complex coupled reactive transport processes, for example scaling of pipes, shall 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 upon heat extraction in combination 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 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 of a thermodynamic model (fluid model, thermodynamic data base) that can be used in PSI GEM software to model CRM and heat extraction
- Implementation of 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 CRM and heat extraction
- (ML-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, master’s degree in chemistry, chemical engineering or related discipline with a strong interest in geoscience applications
- Strong motivation for interdisciplinary research
- Excellent command of spoken and written English (mandatory)
- You are familiar with thermodynamic and/or (geo-)chemical software
- You have experience with programming or scripting languages (e.g. Python, R, Matlab, ...)
We offer
PSI: Our institution is based on an interdisciplinary, innovative and dynamic collaboration. You will profit from a systematic training on the job, in addition to personal development possibilities and our pronounced vocational training culture. If you wish to optimally combine work and family life or other personal interests, we are able to support you with our modern employment conditions and the on-site infrastructure.
MiningBrines: An international network of 32 academic and industrial partners across multiple disciplines offers an innovative doctoral training program to address Europe’s strategic need for sustainable access to critical raw materials, energy gases and renewable energies. You will benefit from an 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 submit their application online and send:
- their CV
- a letter of application
- a 1-page critical summary of an article of their choice
- the name of two contact persons (former teachers or supervisors, who are asked to send a support letter)
- academic credentials
The email subject must be "Application for DC13 position”.
Application Deadline (date and time zone): April 30th, 5PM CET
Applications and enclosures received after the deadline will not be considered.
Expected starting date: 1 October 2026
Please avoid any questions on the status of the selection process. We will inform you as soon as there is an update.
Candidates whose application is not compliant with the requirements above will not be considered.
More information and other vacant positions within the MiningBrines project can be found via the
For further information, please contact Dr Georg Kosakowski, georg.kosakowski@psi.ch.
Paul Scherrer Institute, Human Resources Management, Serdal Varol, 5232 Villigen PSI, Switzerland
Unternehmens-Details
Paul Scherrer Institute
Forschung
