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<b style="font-style:inherit; font-variant-caps:inherit; color:rgba(0,0,0,0.87); font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif; font-size:14px">PhD position in Machine Learning/Computer Vision - Learning from limited labels, <a href="https://machine-learning.uit.no/" target="_blank" rel="nofollow" style="color:rgb(26,115,232)">Machine
Learning Group</a> at UiT The Arctic University of Norway.</b><br>
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We are seeking a PhD Fellow to take an active role in the group's research on developing novel machine learning/computer vision methodology. Special focus in this project will be on developing novel approaches for learning from limited labeled data, such as
few-shot/zero-shot/semi-supervised /self-supervised learning, domain adaptation, and/or deep clustering.</div>
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The position will be part of the already ongoing effort to design deep learning methodology for limited labeled data and will synergize well with some of our recent work [1-3].</div>
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The successful candidate will join the UiT Machine Learning Group, a vibrant group at the "north pole", with excellent national and international connections. </div>
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For details, please see:<span class="Apple-converted-space"> </span><a href="https://www.jobbnorge.no/en/available-jobs/job/206309/phd-fellow-in-machine-learning-computer-vision" target="_blank" rel="nofollow" style="color:rgb(26,115,232)">https://www.jobbnorge.no/en/available-jobs/job/206309/phd-fellow-in-machine-learning-computer-vision</a></div>
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Please contact Michael Kampffmeyer<span class="Apple-converted-space"> (michael.c.kampffmeyer@uit.no)</span><span style="color:rgba(0,0,0,0.87); font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif; font-size:14px"> </span><span style="color:rgba(0,0,0,0.87); font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif; font-size:14px">for
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<font size="2">[1] Trosten, D. J., Løkse, S., Jenssen, R., & Kampffmeyer, M. (2021). Reconsidering Representation Alignment for Multi-view Clustering. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2021.</font></div>
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<font size="2">[2] Nguyen, N., Løkse, S., Wickstrøm, K., Kampffmeyer, M., Roverso, D., & Jenssen, R. (2020). SEN: A Novel Feature Normalization Dissimilarity Measure for Prototypical Few-Shot Learning Networks. In Proceedings of the European Conference on Computer
Vision 2020.</font></div>
<span style="color:rgba(0,0,0,0.87); font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif; font-size:14px"><font size="2">[3] Kampffmeyer, M., Chen, Y., Liang, X., Wang, H., Zhang, Y., & Xing, E. P. (2019). Rethinking knowledge graph propagation for zero-shot
learning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2019.</font></span><br>
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<div style="margin:0px"><span style="">Michael Kampffmeyer</span><br>
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<div style="margin:0px">Associate Professor</div>
UiT Machine Learning Group </div>
<div style="margin:0px; font-family:Tahoma; font-size:13px; text-align:start"><a href="http://machine-learning.uit.no" target="_blank" rel="noopener noreferrer" style="margin:0px">http://machine-learning.uit.no</a><br>
<div style="margin:0px">UiT The Arctic University of Norway</div>
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