Seismic imaging

iCRAG Post-doctoral position Geophysics_PD4
Seismic imaging with massive datasets using sparsifying transformation methods
The rapid recent growth in the scales of seismic and other geophysical datasets offers
unprecedentedly dense sampling of the Earth’s interior, making possible increasingly
detailed and accurate geophysical imaging. It also presents a challenge: the enormous scale
of the computational problems required for the processing, modelling, and inversion of the
“big data”. One issue is that conventional approaches of parametrizing 3D models now begin
to produce prohibitively large computational problems. Another issue is the non-uniqueness
of inverse-problem solutions. In this project, new approaches (wavelet-based sparsifying
transformations, originally developed in applied mathematics) will be applied in order to
solve demanding geophysical problems. New methods will be implemented and tested on
very large seismic (and possibly other) datasets, at a range of scales and with both basic
and applied Earth science targets.
Applications are invited from established and motivated researchers. Qualifications: a PhD in
geophysics or related field is required. Substantial computing and programming experience
and a good command of English are essential. Substantial research experience and proven
publication record are preferred, but recent PhDs with strong relevant expertise will also be
considered. Experience in seismic imaging of the crust and lithosphere is desirable.
The position is fully funded for one year initially with a starting salary of c. €33,975 - €42,394
To apply: e-mail a complete academic CV, a statement of research interests, and the names
and contact details of 3 academic referees to Dr. Sergei Lebedev ([email protected]), with
"Postdoctoral position" in the subject line.
Consideration of applications will begin immediately and continue until the position is filled.
For additional information on the projects please contact the project PI, Dr. Sergei Lebedev
([email protected]).
iCRAG is funded under the SFI Research Centres Programme and is co-funded under the
European Regional Development Fund.