To mitigate seismic risks from subsurface exploitation sites (geothermal energy, subsurface CO2, H2 storage), accurate seismic hazard assessment (SHA) is a necessity. In regions without historical earthquakes, conventional ground motion models cannot be locally calibrated and thus suffer from large uncertainty, rendering them unreliable for the seismic risk assessment of future subsurface activities. The SHAWave project - a collaboration between various Dutch universities and research institutes as part of the DeepNL research programme - will take a new and innovative approach to conduct probabilistic seismic hazard assessment. This approach combines novel computational modeling techniques, based on waveform simulations, with advanced data calibration and risk quantification techniques.

Job Description

Within the SHAWave project, you will develop a state-of-the-art poromechanichal computational model to emulate anelastic (e.g., viscoelasticity) near surface effects. The model will be built on the first-principle-based subsurface simulation tools already developed at TU/e, which are based on state-of-the-art finite element methods. The developed model will be used to assess the validity of other simulators developed in SHAWave and to derive transfer-functions for the anelastic near surface. The most prominent components of your work within SHAWave are:

• To accurately and efficiently model wave propagation in the near-surface layer, you will be using isogeometric analysis (IGA) - an advanced higher-order finite element technique with the potential to yield accurate results on coarse meshes - to solve Biot's model for poroelasticity.
• You will incorporate viscoelastic effects in the poromechanical simulator using a thermodynamically consistent framework which ensures that dissipative mechanisms are incorporated in a physically sound manner.
• You will study the influence of poromechanical effects and anelastic material behavior on the full-scale waveform model developed at one of the project partners.
• You will develop upscaling procedures to convert the anelastic poromechanical model results into (averaged) amplification and damping functions, which help to improve the results of the full-scale waveform model.

Your project will be embedded in the Energy Technology section at the Department of Mechanical Engineering of the Eindhoven University of Technology (TU/e). You will work together with the partners in the SHAWave project to ensure that the developed poromechanical model is successfully integrated.

• You have experience with or a strong background in applied mathematics, physics and computational engineering. Preferably, you finished a Master's program in the areas of Mechanical Engineering, Civil Engineering, (Applied) Physics, (Applied) Mathematics, Computer Science, or equivalent.
• You are a proficient programmer, willing to dedicate a substantial part of your time to high-performance computing software development.
• You have good communication skills and the attitude to participate successfully in the work of a research team.
• You have good command of the English language (knowledge of Dutch is not required).
• You are a talented and enthusiastic young researcher.

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,770 max. €3,539).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.