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 (http://github.com/odlgroup/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 http://arxiv.org/abs/1707.06474 and http://arxiv.org/abs/1704.04058 and the blog-post at http://adler-j.github.io/2017/07/21/Learning-to-reconstruct.html for further details. Part of the research may include industrial (Elekta and Philips Healthcare) and clinical (Karolinska University Hospital) collaboration.

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