Open Research Position in Deep Learning for Computer Vision

An opening is available for an OPEN RESEARCH POSITION at the University of Ljubljana in the area of deep learning for computer vision. The opening is available within a national research project funded by the Slovenian Research Agency (ARRS). The goal of the project is to develop deep learning models able to infer volumetric part-based models from visual data, e.g., depth images, point clouds, intensity images, etc.

The appointment is from January 1st, 2019 (may be delayed a few (1-3) months if needed) until June 30th, 2020 with a possible extension.

If the candidate does not hold a PhD degree, enrollment into the Doctoral School of the University of Ljubljana is also possible.

Work description for Open research Position

The candidate is expected to

  • Conduct research in the scope of a fundamental ARRS project
  • Develop deep learning solutions for the recovery volumetric models from visual data
  • Publish results in peer reviewed vision-oriented journals and conferences
  • Collaborate with students and research staff on related projects

Expected qualifications

  • MSc or PhD degree in computer science or related fields
  • Outstanding programming skills, e.g., Python, Matlab, C++
  • Experience with deep learning frameworks, e.g., Keras, PyTorch, Caffe
  • Familiarity with computer vision tools and libraries, e.g., OpenCV, VLFeat
  • Good track record – publications in SCI indexed journals and top-tier conferences
  • Excellent oral and written communication skills (in English)

How to apply

Interested candidates should send a CV with a detailed description of skills and research experience and a cover letter with the e-mail subject [ARRS SQ: Research application] to Assoc. Prof. Peter Peer and Assoc. Prof. Vitomir Struc. Review of applications will continue until the position is filled. Feel free to contact us if you have any questions.

Project web-site

Note: Before you apply for this position, you should have good number of SCI/ SCIE indexed research papers with reference to recent SCI/ SCIE indexed journals list 2018 and/ or review paper. Alternatively, you should have published your research work in core ranked conferences.

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