Research Associate for the Project “Passive Seismic Imaging of Geothermal Reservoirs with Dark Fibers” in the project RUBADO: Geothermal Reservoir Monitoring and Seismic Imaging with Dark Fibers in the Upper Rhine Graben § 28 Subsection 3 HmbHG
InstitutionFaculty of Mathematics, Informatics and Natural Sciences, Department of Earth System Sciences, Institute of Geophysics
Salary level
Start date01.08.2026, fixed until 31.07.2029 (This is a fixed-term contract in accordance with Section 2 of the academic fixed-term labor contract act [Wissenschaftszeitvertragsgesetz, WissZeitVG]).
Application deadline25.05.2026
Scope of workpart-time
Weekly hours75 % of standard work hours per week
Your responsibilities
Duties include academic services in the project named above. Research associates may also pursue further academic qualifications outside of their work responsibilities. They may also pursue doctoral studies outside of working duties.
The position is part of the project “RUBADO: Geothermal Reservoir Monitoring and Seismic Imaging with Dark Fibers in the Upper Rhine Graben”, funded by the Federal Ministry for Economic Affairs and Energy of Germany (BMWE). RUBADO is a collaboration between the University of Hamburg, the Karlsruhe Institute of Technology and Geotomographie GmbH. RUBADO investigates the innovative use of seismic sensing networks and distributed acoustic sensing (DAS) on existing urban and rural fiber-optic infrastructure for the high-resolution monitoring and imaging of geothermal reservoirs. The project aims to advance cost-effective, minimally invasive, and scalable techniques for subsurface characterization, reservoir safety, and long-term environmental stewardship in geothermally active regions. RUBADO focuses on existing geothermal infrastructure in the Upper Rhine Graben, leveraging extensive telecom “dark fiber” networks to set new standards in geoscientific imaging and monitoring, supporting the sustainable development and societal acceptance of geothermal energy solutions.
The position is situated within the seismology group at the Institute of Geophysics, University of Hamburg. The group specializes in ambient noise seismology, passive imaging, seismic interferometry, distributed acoustic sensing, and modern data-driven analysis techniques, including machine learning. Research focuses on understanding seismic noise sources, imaging near-surface and crustal structures, and monitoring structural changes in Earth materials.
The successful candidate will focus on the development and application of passive seismic imaging methods using ambient seismic noise recorded on dark-fiber DAS networks. The primary research objective is the determination of shallow and intermediate-depth subsurface structures along several DAS deployments in Karlsruhe and the Upper Rhine Graben. Tasks include the development, implementation, and testing of advanced methods for beamforming and surface-wave tomography, the inversion of frequency-dependent measurements to derive S-wave velocity profiles (e.g., VS30), and the integration of ambient-noise interferometry to generate tomographic models along the fiber-optic lines. The successful candidate will actively collaborate with project partners, validate DAS-based results using classical sensor networks, and contribute to the development of open-source workflows.
Responsibilities further include contributing to field deployments of seismic sensors, participating in project meetings, presenting research at international conferences, preparing publications in peer‑reviewed journals, and contributing to open-science dissemination efforts within the RUBADO consortium.
The successful candidate may become a member of the School of Integrated Climate and Earth System Sciences (SICSS), which supports doctoral researchers through training, mentoring, and career development.
Your profile
A university degree in a relevant field.
We welcome applications from candidates who fulfill the following criteria:
1. a completed research‑oriented Master’s degree in a relevant field (e.g., Geophysics, Physics, Engineering); the degree must be completed at the time of recruitment
2. a strong academic record relevant to the project
3. proven background in seismic or elastic wave propagation and digital signal processing
4. experience in at least one of the following areas: ambient seismic noise analysis and seismic interferometry inverse problems or optimization methods, or fiber‑optic/distributed acoustic sensing (DAS) or big‑data analysis experience in multiple areas is an advantage
5. experience developing scientific workflows in Python or a comparable scientific programming environment
6. willingness to participate in occasional field campaigns
7. excellent command of English, both spoken and written, with the ability to communicate effectively in an international research environment
8. ability to work reliably, independently, and collaboratively in an interdisciplinary research environment
We offer
9. Reliable remuneration based on wage agreements
10. Continuing education opportunities
11. University pensions
12. Attractive location
13. Flexible working hours
14. Work-life balance opportunities
15. Health management, EGYM Wellpass
16. Educational leave
17. 30 days of vacation per annum
Universität Hamburg—University of Excellence is one of the strongest research educational institutions in Germany. Our work in research, teaching, educational and knowledge exchange activities is fostering the next generation of responsible global citizens ready to tackle the global challenges facing us. Our guiding principle “Innovating and Cooperating for a Sustainable Future in a digital age” drives collaboration with academic and nonacademic partner institutions in the Hamburg Metropolitan Region and around the world. We would like to invite you to be part of our community to work with us in creating sustainable and digital change for a dynamic and pluralist society.
The University of Hamburg is committed to equity. Diversity enriches our university life, whether in our studies, research, teaching, education, or workplace. We therefore welcome all applications, regardless of gender, gender identity, sexual orientation, ethnic or social background, age, religion or belief, disability, or chronic illness.
Severely disabled and disabled applicants with the same status will receive preference over equally qualified non-disabled applicants.