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This PhD stipend is funded by the Pioneer Centre for Artificial Intelligence’s Collaboratory, Signals and Decoding. The Pioneer Centre for AI is located at the University of Copenhagen, with partners at Aarhus University, Aalborg University, The Technical University of Denmark, and the IT University of Copenhagen. There will be a cohort of PhD students starting during the fall of 2023 across the partner universities. PhD students at the Pioneer Centre for AI will have extraordinary access computing resources, to international researchers across many disciplines within computer sciences and other academic areas, as well as courses and events at the centre, and meaningful collaboration with industry, the public sector, and the start-up ecosystem.
Centre website: www.aicentre.dk
To date, most successful applications of deep learning in signals and decoding are based on supervised learning. However, supervised learning is contingent on the availability of labelled data, i.e., each sample has a semantic annotation. The need for labelled data is a serious limitation to applications at scale and complicates the maintenance of real-life supervised learning systems.
The typical situation is that unlabelled data is abundant, and this has given rise to paradigms such as semi-supervised and self-supervised learning (SSL). Both directions in SSL are based on combining large amounts of unlabelled data with limited labelled data. While semi-supervised learning invokes generative models to learn representations that support learning with few labels, self-supervised learning is based on supervised learning with a supervisory signal derived from the data itself.
The goal of this PhD study is to develop novel semi-supervised and self-supervised methods for modeling signals of various modalities (e.g., speech, audio, vision, text) and analyse the complexity of the developed models. The PhD student during the study is further provided with opportunities to do research at other units and the headquarter of the Pioneer Centre as well as abroad.
The PhD candidate is expected to have:
You may obtain further information from Professor Zheng-Hua Tan, Department of Electronic Systems, phone: +45 99 40 86 86, email: email@example.com, concerning the scientific aspects of the stipend.