Skip to main content
Bayi Glacier in Qilian Mountain, China (Credit: Xiaoming Wang, distributed via

Job advertisement PhD Position in Machine Learning Seismology and Induced Earthquakes

EGU logo

European Geosciences Union

PhD Position in Machine Learning Seismology and Induced Earthquakes

PhD Position in Machine Learning Seismology and Induced Earthquakes

Swiss Seismological Service logo

Swiss Seismological Service

The Swiss Seismological Service (SED) at the Department of Earth Sciences at ETH Zürich is the agency responsible for earthquake monitoring as well as hazard and risk assessment in Switzerland. The SED conducts a broad range of fundamental and applied research in earthquake science and is involved in several projects in the field of seismic monitoring and imaging, earthquake hazard and risk evaluation, and induced earthquake analysis.


Zurich, Switzerland


Relevant divisions
Energy, Resources and the Environment (ERE)
Natural Hazards (NH)
Seismology (SM)


Student / Graduate / Internship


Required education

Application deadline
15 June 2024

7 May 2024

Job description

The Swiss Seismological Service (SED) at the Department of Earth Sciences at ETH Zürich invites applications for a fully funded 4-year PhD position in Machine Learning Seismology and Induced Earthquakes. The preferred starting date for this position is June – September 2024. This PhD position is supported by a Swiss National Science Foundation (SNSF) funded project EFFSIMMSI, led by Dr. Peidong Shi and collaborators at ETH Zurich and INGV.

The PhD student will focus on constructing and training advanced machine learning models tailored to characterize induced earthquakes recorded by various instruments, including distributed acoustic sensing, acoustic emission sensors, and geophones. With these efforts, the PhD candidate will improve the current state-of-the-art of real-time seismic monitoring and induced earthquake forecasting by implementing advanced machine-learning techniques and integrating physical understandings of rupture dynamics. The PhD candidate will apply the developed methodologies and models to various geological test sites to extract high-resolution earthquake catalogs, analyze rock rupture mechanisms, and benchmark different induced earthquake forecasting models.

We are seeking a highly motivated candidate with a strong interest in machine learning, seismic monitoring and earthquake seismology. The ideal candidate should:

  • A Master’s degree in Earth Sciences / Physics / Mathematics / Computer Sciences or a related discipline is required. Applicants must have obtained their Master’s degree by September 2024
  • A strong foundation in analyzing large datasets and machine learning is highly desirable for this position
  • Proficiency in modern scientific programming languages (e.g., advanced Python, C, CUDA etc) and parallel computing would be advantageous
  • Strong background and experience in computational methods and earthquake monitoring would be an asset
  • The PhD student will be required to work as part of an international team. We presuppose abilities in coherent scientific teamwork, excellent communication skills (spoken and written English) and the capability of a good work organization as far as precise way of working

The work will be conducted at SED under the supervision of Dr. Peidong Shi and Prof. Stefan Wiemer. The student will also benefit from interdisciplinary and interinstitutional collaboration with international experts in machine learning, seismic monitoring/imaging, statistical seismology, and geomechanical modelling. Project team members include Dr. Federica Lanza (ETH Zürich), Dr. Luigi Passarelli (INGV), and Dr. Antonio Pio Rinaldi (ETH Zürich).

How to apply

We look forward to receiving your online application by June 15th, 2024, with the following documents:

  • Motivation Letter (no more than 2 pages)
    • describe your research achievements and research interests
    • demonstrate your interest and suitability for the offered position
  • Full CV
  • Undergraduate and graduate transcripts
  • Contact details of two referees

Please note that we exclusively accept applications submitted through our online application portal (do not send any applications by e-mail). The review process is scheduled to commence on May 24th, 2024, and will continue until the position has been filled. Applications received before May 24th will be given full consideration. Therefore, we encourage applicants to submit their applications as early as possible. Applications via email or postal services will not be considered.

Application Website:!/?lang=en