奥地利因斯布鲁克大学应用数学方向博士后职位

Research

Our research is located at the intersection of mathematics, signal processing and machine learning. In particular we are interested in the learning of representation systems (dictionaries) providing compact (sparse) descriptions for high-dimensional data classes from a theoretical and algorithmic point of view and in applying these dictionaries to data processing and analysis tasks. Our main tools come from sparse approximation, geometric functional analysis (concentration of measure), harmonic analysis and optimisation. More information can be found on the website, indicated below.



Environment

The project is embedded into the Applied Mathematics Group at the Department of Mathematics of the University of Innsbruck, which performs research on inverse problems, computed tomography, photoacoustic imaging, learning theory and compressed sensing and is involved in the interdisciplinary doctoral school on high performance computing. On an international level the project is well integrated into the dictionary learning, sparse approximation, harmonic analysis and compressed sensing communities and involves cooperations with groups in Rennes (FR), Paris (FR), Edinburgh (UK), Haifa (IL), Vienna (AT), etc. Working language is English but (readiness to acquire) some German skills will be useful for every day life in Innsbruck.



Offer

To the successful candidate will be offered a research position of up to 6 years, salary about 48.000EUR/year gross on a 40h/week basis, rising to 53.000EUR/year in the 4th year, part-time employment on request. The candidate is further supported with an autonomous travel budget of about 5.000 EUR/year and the University of Innsbruck is offering a variety of additional employee benefits. Teaching is not required but possible. We provide both individual guidance and independent career development. The project started June 1, 2015, and the starting date for the position is at earliest convenience.



Qualifications



Interested candidates with a mathematics related PhD and strong mathematical skills in one or more of the following fields - geometric functional analysis (measure concentration, probability theory), machine learning (dictionary learning), sparsity, approximation theory, optimisation, harmonic analysis, compressed sensing - are invited to apply, by electronically submitting (in pdf format) a short motivation letter, a cv including list of publications and 2 to 3 recommendation letters to karin.schnass@uibk.ac.at. Preferably the reference letters should be sent directly by the referees. Processing of applications is on the fly and all complete (!) applications will be fully considered until the position is filled.