PhD Position (f_m_x) - Physics-based machine learning for optimal experimental design
The Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences is the national centre for research into the geosphere. With around 1,650 employees, we develop a sound understanding of systems and processes of the solid Earth as well as strategies and options for action to counter global change, understand natural hazards and sustainably secure energy and raw material requirements.
For section 4.5 "Subsurface Process Modelling" (department 4 “Geosystems”), we are looking for a:
PhD Position (f_m_x) - Physics-based machine learning for optimal experimental design
Reference Number 9626
Exploring optimal experimental design utilizing physics-based machine learning for geothermal operations
Are you seeking a PhD project at the interface between geoscience, machine learning and mathematics, with an application to the highly relevant topic of induced seismicity? Then a position in this project might be appealing to you. The aim of the project is the further development and optimization of hybrid artificial intelligence systems. A specific focus is on sparse data applications and the reliable incorporation of physical knowledge, to produce explainable models. The project focuses on the use of AI methods in procedures for determining sensitivities, uncertainties and an optimal experimental design. The topic of induced seismicity is important for the further development of technologies in the field of geothermal energy, resulting in a high social relevance of the project.
The PhD position is subject to approval by third-party funders.
Your responsibilities:
Development of new strategies to generate reliable machine learning models for the simulation of thermo-hydro-mechanical (THM) processes
Generation of predictive maps to evaluate the potential of induced seismicity
Further development of the code basis
Presentation of the results on conferences and publication in peer-reviewed journals
Your qualifications:
Master degree or equivalent in mathematics, computer science or geophysics or in related subjects
Interest in research and applications in the field of induced seismicity
Programming skills in Python as well as experience in the field of machine learning
Good English language skills
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