Doctoral position at RICAM in numerical harmonic analysis and PDE for image processing

RICAM, the Johann Radon Institute for Computational and Applied Mathematics (Austrian Academy of Sciences), is looking for 1 doctoral student in applied and computational mathematics interested in pursuing research in computational harmonic analysis and partial dif-ferential equations for advanced image processing. We emphasize the interdisciplinary approach which will involve both a variety of mathematical tools and applications in art restoration. The student will be a member of the WWTF project “Five Senses - Call 2006″, Mathematical Methods for Image Analysis and Processing in Visual Arts at RICAM, Linz, Austria.

Deadline for applications: May 31, 2007

Starting date of the PhD: November 1

The salary is determined according to the rules of the Austrian Research Fund FWF (http://www.fwf.ac.at/de/projects/personalkostensaetze_2007.html), i.e., 30.860,00 Euro/year before tax.

Work location: RICAM, Linz, Austria.

Applications should be addressed to Dr. Massimo Fornasier
(massimo.fornasier@oeaw.ac.at) by an email with title “Ph.D. position” and
they should consist of:

• a presentation letter
• curriculum vitae et studiorum (including grades for each exam)
• diploma thesis, if already finished, title and abstract otherwise
• up to two letters of recommendation (to be scanned and included in the email)

The ideal candidate has a good background in functional and numerical analysis.

We attach further information about the project and the institute.

About the project:
(http://www.math.princeton.edu/~mfornasi/fresken.htm)

The time requirements for a PhD thesis is typically in the range of 3 years. The doctoral studies will be focussed (although not limited) on variational calculus and inverse problems for image reconstruction and applications in art restoration.

In particular, we are interested in investigating the relations between generalizations of the Mumford-Shah functional on vector valued functions and discrete functionals promoting sparsity in sequence spaces of wavelet/curvelet coefficients. Minimizers of such functionals model the
restoration of corrupted images. Efficient and stable algorithms will be studied for the numerical approximation of the minimizers. Depending on the particular interests of the doctoral student, related investigations in compressed sensing and learning theory can also be pursued, and medical applications in brain imaging can be also addressed.

Information on the institute can be found at:
http://www.ricam.oeaw.ac.at/