Back to all jobs
Visible on IKONS todayNewPopular
OverijsselHybrid40 hours/week6-12months
The transition toward sustainable offshore resource management and subsurface utilization is driving an unprecedented demand for reliable monitoring technologies.
- Offshore environments present unique challenges for geophysical observations due to their limited accessibility, high operational costs, and sparse instrumentation.
- The need to detect and characterize seismic activity in near real time is becoming increasingly important for ensuring operational safety and supporting informed decision-making in offshore settings.
- This project will develop innovative methodologies to integrate In-Well Distributed Acoustic Sensing (In-Well DAS) data with observations from offshore seismological stations.
- The aim is to enable on-site near-real-time offshore seismic monitoring.
- Existing In-Well DAS fiber-optic cables can be transformed into dense arrays of seismic sensors.
- Combining these complementary observations through advanced signal processing, machine learning, and physics-based simulations, the project aims to improve event detection, localization, and characterization capabilities in challenging offshore environments.
- The resulting framework will establish scalable workflows for seismicity monitoring applicable to offshore regions.
- Results will be disseminated through high-quality scientific publications, conference presentations, open-source algorithms, and collaborations with academic, governmental, and industry partners.
What you do
- Collaborate closely with researchers from a national meteorological institute and a national energy company.
- Work within a large European consortium led by a research institute.
- Join an interdisciplinary research environment, working closely with authorities in seismology, geophysics, signal processing, and geospatial data science.
- Contribute to the development of next-generation monitoring solutions that bridge emerging sensing technologies and established seismological practices.
- Opportunities to collaborate with leading national and international partners.
- Contribute to teaching and supervision activities related to geophysical monitoring and data integration.
Profile
- A (soon-to-be-obtained) PhD in seismology, DAS, deep learning related to Earth sciences, or a related field.
- Good command of spoken and written English.
- Ability to deal with and process seismological time series datasets and computer programming, e.g., with Python, MATLAB, C and/or Fortran.
- Working with a major machine-learning framework (e.g., PyTorch, TensorFlow, JAX).
- Familiarity with inverse theory is desirable but not essential.
- Curiosity in numerical methods for partial differential equations, big data management, and dealing with supercomputing facilities.
- A socially engaged, independent and creative researcher with good conceptual, communication, problem-solving and organizational skills.
- An interest in engaging in team-based collaborations.
How to apply
View the full assignment text and application details once your tailored application is ready.
Order a tailored application to view the full assignment and application details.
More context, less searching.
You get enough context to judge whether this job is relevant. The full brief, client details and next steps stay available inside the app.