Don't miss out! - Deadline for application is 08.11.2024
There is still time to apply for an exciting opening for a PhD Candidate in Computational Seismology in CGF Work Package 7.
The successful candidate will work in a team using High Performance Computing tools to develop methodologies for seismic inversion and imaging with application to properties and structure of the Earths Lithosphere. The team cooperates internationally and short/long term stays with research groups outside Europe is expected.
As a PhD candidate you will work at the Department of Geosciences (IGP) and be a part of the Centre for Geophysical Forecasting (CGF) at NTNU.
The CGF periodically issues invitations to apply for funded PhD and PostDoc positions. Being a strongly interdisciplinary centre, we are looking for entrepreneurial students with a wide variety of interests and backgrounds, from electronic engineering to fibre optics, from geophysics to acoustic wave propagation modellers, from heterogeneous computing to statistical and data scientists. Successful applicants will work at the CGF premises at NTNU in Trondheim as part of our international team of key researchers. The CGF PhD research fellowships are hosted by several departments at NTNU: Computer Science, Electronic Systems, Geoscience and Petroleum and Mathematical Sciences. The Centre has close contact with industry partners as well as research partners NORSAR and Jamstec in Japan.
PhD students will use and develop advanced models and methods for combining diverse geophysical data to effectively monitor the earth. PhD students will be involved in the planning of new surveys and the acquisition of valuable geophysical information to improve forecasts and provide important decision support for the various application domains of the CGF.
The CGF is developing novel methods for the cost-effective use of fibre optic cables, creating Distributed Acoustic Sensing (DAS) systems for Earth monitoring. Such DAS data complement traditional geophysical data sources such as seismic waveform measurements, electromagnetic data, and geomodelling information.
To extract the important variables from massive spatio-temporal geophysical data, the CGF will work on heterogeneous platform computing and AI-based approaches for feature extraction, enabling efficient monitoring and early warning systems in the various geosciences applications.
PhD research work will be led by supervisors with strong scientific profiles in the specific disciplines at the CGF.
The CGF is determined to deliver research-based innovation, and it will strongly stimulate PhD candidates to create and develop innovative ideas into business potential both for the Centre partners as well as in spin-off companies. The key innovation areas of the CGF are in CCS management, hydrocarbon production monitoring and geohazards monitoring and forecasting.