Duration: 3 years
Category: Research
Type: PhD thesis
Contacts: alexandre.pitti@cyu.fr sofiane.boucenna@cyu.fr

The Neurocybernetic team of ETIS Lab (CNRS, CY Cergy-Paris University, ENSEA) is seeking applicants for a fully funded PhD place providing an exciting opportunity to pursue a postgraduate research in the fields of bio/neuro-inspired robotics, ethology, neuroscience.
Webpage: https://www.etis-lab.fr/neuro/

This PhD is funded by the French ANR, under the 4 years’ project “Nirvana”, on **Sensorimotor integration of variability during birdsong learning**. Partners are University Paris Nanterre, Paris-Saclay University, CY Cergy-Paris University and CNRS LS2N.

Motor variability, by allowing the exploration of the motor space, is an essential component of how sensorimotor circuits change across the learning course and may adapt to different conditions. Yet, knowledge remains sparse on how the variability of the input model contributes to the efficiency of sensorimotor integration during both speech acquisition and birdsong learning. This proposal will shed light on the impact of behavioral variability on learning skills and on the neurobiological processes at play to eventually feed neurocomputational models of human speech learning.

This PhD will propose new conceptual approaches to design an interactive bird robot that will be used both to teach and to learn dynamically from social interactions with a live bird. An artificial neural model, developmental and brain-inspired, will learn the sound structure in real time and without explicit supervision. Until now, AI models for developmental learning of vocalizations have been solely validated by comparison against a human-annotated corpus and not yet via direct sensorimotor interactions with living animals.

The PhD lasts for 3 years and includes a small teaching component.

To apply, send us an email first.
Please include:
1. A statement of research interests
2. A detailed CV
3. A transcript of your diplomas
4. Your Master/Diploma thesis, and any draft or published papers

Contact:
Prof Alex Pitti, alexandre.pitti@cyu.fr
Prof assistant Sofiane Boucenna, sofiane.boucenna@cyu.fr

Apply for this position

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