Postdoctoral Researcher Integrating In-Well DAS with Seismological Stations for Offshore Near-real-time Monitoring

Postdoctoral Researcher Integrating In-Well DAS with Seismological Stations for Offshore Near-real-time Monitoring
University of Twente
Enschede, Netherlands
€ 4,251 - € 5,760 per month gross
Your challenge
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. At the same time, the need to detect and characterize seismic activity in near real time is becoming increasingly important for ensuring operational safety, understanding subsurface processes, and supporting informed decision-making in offshore settings. Recent advances in sensing technologies offer new opportunities to improve monitoring capabilities and provide a more comprehensive view of dynamic processes occurring beneath the seabed.
This project will develop innovative methodologies to integrate In-Well Distributed Acoustic Sensing (In-Well DAS) data with observations from offshore seismological stations, currently under development, enabling on-site near-real-time offshore seismic monitoring. The existing In-Well DAS fiber-optic cables can be transformed into dense arrays of seismic sensors, complementing the offshore seismic stations and potentially increase the detection limits. By 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.
You will collaborate closely with researchers from KNMI and directly with EBN, and you will work within a large Horizon Europe CETP consortium led by NORSAR. You will join an interdisciplinary research environment, working closely with authorities in seismology, geophysics, signal processing, and geospatial data science. As part of a dynamic team of researchers, Doctoral candidates, and external collaborators, you will contribute to the development of next-generation monitoring solutions that bridge emerging sensing technologies and established seismological practices.
Your 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, and an interest in engaging in team-based collaborations
Apply Now
Deadline 20 November
Don't forget to mention EuroScienceJobs when applying.
Share this Job
More Job Searches
Netherlands
AI Scientist
Academic
Computing/Programming
Data Science
Earth Science
Geophysics
Maths and Computing
On-site
Postdoc
University of Twente