In the context of a new Swiss NSF grant, we seek a PhD student to work in the general area of neural architectures for speech technology. The particular focus of this thesis will be on physiological models of speech prosody, and how such models can be integrated into deep learning solutions. The research will build on work done over the past few years at Idiap on creating tools for physiologically plausible modelling of speech. The current "toolbox" contains rudimentary muscle models and means to drive these using conventional (deep) neural networks. Whilst we have focused so far on prosody (actually intonation), the application is open ended; the main goal is to generalise neural modelling to more closely mimic biological systems. The group also tries to use rigorous Bayesian techniques where possible.