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 (sergei@cp.dias.ie), 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 (sergei@cp.dias.ie). iCRAG is funded under the SFI Research Centres Programme and is co-funded under the European Regional Development Fund. www.iCRAG-centre.org