Postdoctoral fellowship in Image Reconstruction/Deep Dictionary Learning (S-2017-1165)

The 2-year position includes research & development of theory and algorithms that combine methods from machine learning with sparse signal processing for joint dictionary design and image reconstruction in tomography. A key element is to design dictionaries that not only yield sparse representation, but also contain discriminative information. Methods will be implemented in ODL (, our Python based framework for reconstruction which enables one to utilize the existing integration between ODL and TensorFlow.

The research is part of a larger effort that aims to combine elements of variational regularization with machine learning for solving large scale inverse problems, see the arXiv-reports and and the blog-post at for further details. Part of the research may include industrial (Elekta and Philips Healthcare) and clinical (Karolinska University Hospital) collaboration.

Job location: 
Department of Mathematics
KTH Royal Institute of Technology
10044 Stockholm
Contact and application information
Friday, December 1, 2017
Contact name: 
Ozan Öktem
Contact email: