The new DFG International Research Training Group (IRTG) 2379 builds on a unique consortium, at RWTH Aachen University with its Aachen Institute of Advanced Study in Computational Engineering Science, and at the University of Texas at Austin with its Institute for Computational Engineering and Sciences. The projects are embedded in the field of modern inverse problems and introduce a new innovative perspective into the education of future scientists and engineers.
This sub-project be advised jointly by Prof. Florian Wellmann at RWTH Aachen and Prof. Omar Ghattas at UT Austin. In the context of inverse problems, the field of geosciences provides formidable challenges: the parameter space is large, the applied mathematical models are highly complex, and the available data of diverse quality. We seek here an outstanding candidate to investigate novel geological modeling approaches to address challenging geophysical inverse problems in subsurface applications, for example groundwater and geothermal exploration.
The specific aims of this project are:
- Obtain novel schemes for combinedgeological modeling and geophysical inversion
- Address challenging geophysical calibration and inverse problems
Your Profile: Requirement for this position is a master's degree in Geophysics, Applied Geosciences, Physics, or a similar subject with a superior academic record. Practical programming experience in Python or C as well as with parallelization and high performance computing are of advantage. Familiarity with UNIX operating system would be ideal. Excellent written and spoken English language skills are required.
Our offer: The candidate will be employed as a regular employee and must meet required personal qualifications. This is a full-time position with salary according to civil service pay scale TV-L E 13. The expected appointment period is three years. Full involvement in the IRTG activities, including joint RWTH-UT colloquia, annual workshops and schools, and short courses is expected. A six-month research stay at University of Texas in Austin is part of the training program. Applications are being reviewed now (until filled) and envisaged s tarting date for the position is October 1st.
Please send application documents as a single PDF file containing CV, letter of motivation and research interests, transcript of records, and two letters of recommendation to firstname.lastname@example.org.