I've updated the list of MIR PhD theses to include the recent work by Antti Eronen on Signal Processing Methods for Audio Classification and Music Content Analysis. Antti covers a broad range of fascinating audio content processing topics such as: instrument classification, classification of ambient environments/backgrounds (libraries, cars, ...), chorus detection, and meter analysis.
Seems like I'm the list is still far from complete. As the following two theses indicate. If you know of any more that I'm missing please let me know. (Thank you Arijit Biswas for your help!)
One that I missed is the work of Michael J. Bruderer on Perception and Modeling of Segment Boundaries in Popular Music. Which describes an interesting series of experiments in which Michael explores which cues listeners use when segmenting music and how they can be modeled.
Another older one I've added is the work of Olivier Gillet Transcription des signaux percussifs. Application à l'analyse de scènes musicales audiovisuelles. Olivier joined Google after his PhD where he worked on the optimization of Google's ad product and on technologies now being used by Google China Music. Olivier is now joining us at Last.fm's to work on fun next generation MIR technologies.
I would also like to mention the Master thesis Implementing a scalable music recommender by Erik Bernhardsson. I really like how Spotify has given him access to their data and let him publish the results. Seems like Spotify was also very happy with his work as they have hired him.