University of Hamburg

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.

Homepage: https://www.uni-hamburg.de/

Your responsibilities

Duties include academic services in the project named above. Research associates may also pursue independent research and further academic qualifications.

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). The project 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 will be situated in the seismology group at the Institute of Geophysics of the University of Hamburg. The group specializes in ambient noise seismology and innovative seismic instrumentation, with research focusing on the understanding of seismic noise sources, imaging, and monitoring of structural changes in Earth materials. Advanced sensors and machine learning techniques are applied to investigate the near subsurface.

The successful candidate will lead efforts in seismic imaging of the shallow subsurface using ambient seismic noise and will calibrate distributed acoustic sensing measurement points. They will support the deployment of DAS and classical seismic sensors in the field and aid the development of machine learning models for event detection and classification. Responsibilities include analyzing large-scale DAS data sets, comparing results with classical sensor deployments, developing and verifying methodologies for noise-based crustal imaging in the geothermal context, and calibrating measurement points using ambient noise data. The candidate will also have the opportunity to help supervise and mentor an upcoming PhD candidate within the project.

The successful candidate can become a member of the School of Integrated Climate and Earth System Sciences (SICSS), which provides academic and soft skills training, as well as career planning support. They will participate in national/international conferences and regular project meetings with the RUBADO consortium.

Your profile

A university degree in a relevant field.

We welcome applications from candidates who fulfill the following criteria:

• a completed doctoral degree (PhD) in geophysics, physics, engineering, geoinformatics, or a closely related discipline by the time of appointment is desirable
• an outstanding academic track record
• advanced expertise in seismic imaging, ambient noise analysis, or distributed acoustic sensing (DAS), and a strong interest in methodological innovation
• demonstrated programming proficiency and experience with workflow automation (e.g., Python)
• experience in analyzing large-scale seismic datasets (e.g., DAS or large-N arrays), and interest or experience in applying machine learning to time-series or geophysical data
• excellent command of English, both spoken and written, and ability to communicate effectively in an international research environment
• high level of independence, scientific curiosity, reliability, and teamwork skills
• commitment to open science; experience with open-source scientific development and outreach to external stakeholders (industry, regulators, broader community) is an advantage

Outstanding candidates will demonstrate high intrinsic motivation, a strong sense of responsibility, creative scientific thinking, and excellent social and collaborative skills.

We offer

• Reliable remuneration based on wage agreements
• Continuing education opportunities
• University pensions
• Attractive location
• Flexible working hours
• Work-life balance opportunities
• Health management, EGYM Wellpass
• Educational leave
• 30 days of vacation per annum

Use only the online application form (see https://www.uni-hamburg.de/stellenangebote/ausschreibung.html?jobID=139bde655f81f189dc1ef3aef9a5f8a1dade9d47) to submit your application with the following documents:

• cover letter, in which you describe your motivation and qualifications for the position
• CV, including relevant competences, skills and publication list
• copies of degree certificate(s) for previous studies (Bachelor, Master, PhD); please indicate expected date of graduation if your PhD degree is not yet completed
• contact information of two references

If you experience technical problems, send an email to bewerbungen@uni-hamburg.de.