Principal Investigator: Prof. Xavier Serra leads research on advanced learning techniques to enhance automatic music and audio processing: sound and music description, information retrieval, singing voice synthesis, audio source separation.
Email: xavier.serra@upf.edu
Web: https://www.upf.edu/web/xavier-serra
Brief Theme Description
The Department of Engineering at UPF invites applications for a fellowship focused on the development of AI methodologies for understanding and processing music and audio content, focusing on applications in creation, distribution, education, and preservation. The fellow will be hosted by the Music Technologies Research Group (MTG). The appointed fellow will drive research that explores innovative AI methodologies that drive advancements in music and audio understanding, with applications spanning creation, distribution, education, and preservation.
Keywords: Sound and Music Computing; Music Information Retrieval; Computational Musicology.
Qualifications:
- PhD in Artificial Intelligence, Machine Learning, or a related field.
- Expertise in at least one of the following: multimodal data processing, reinforcement learning, or computational creativity.
- Proven ability to bridge theoretical AI research and real-world applications.
- Excellent collaboration and communication skills to work in interdisciplinary teams.
Infrastructure: The Department of Engineering at UPF houses infrastructure for both engineering work (computing, specialised audio-visual equipment – VR, audio, etc.). The HPC covers four main layers: centralized storage and remote backup (housing 3PB of primary storage, 121.64 TB 9 on backup), supercomputing (GPU: 832 CPU cores with 40 Nvidia L40s GPUs across 13 GPU computing nodes), private cloud virtualization (1.5 TB RAM, 10Gbit enabled) and microservices infrastructure.
Possible Secondments: BMAT
