Industrial doctoral student position in a WASP-financed project at Ericsson Research in Stockholm.
Applications will be reviewed as they are received.
Project summary
Representation learning is a vital component of large language/sequence models. It implicitly captures hidden structures of input sequences and exhibits great performance when predicting the next token. Mobile networks can actively benefit from this capability thus ushering a new era of transmitters and receivers powered by AI thus reducing communication costs. Would you like to be a part of this revolution?We are looking for an enthusiastic candidate with solid course track record and passion for research to conduct industrial PhD studies within the area of representation learning in semantic communication networks through a combined framework of self-supervised learning techniques with formal strategies from the Age of Information to introduce interpretability but also scalability and performance to this new communication paradigm.