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9 janvier 2020

Machine learning for neural speech decoding

Catégorie : Post-doctorant

12-month Postdoctoral research position in machine learning for neural speech decoding

Place: GIPSA-lab(CNRS/UGA/Grenoble-INP) in collaboration with BrainTech laboratory (INSERM). Both laboratories are located on the same campus in Grenoble, France.


Team: CRISSP team@GIPSA-lab (Cognitive Robotics, Interactive System and Speech processing).



This position is part of the ANR (French National Research Agency) BrainSpeak project aiming at developing a Brain-Computer Interface (BCI) for speech rehabilitation, based on large-scale neural recordings. This post-doc position aims at developing new machine learning algorithms to improve the conversion of neural signals into an intelligible acoustic speech signal.


Investigate deep learning approaches to map intracranial recordings (ECoG) to speech features (spectral, articulatory, or linguistic features). A particular focus will be put on 1) weakly or self-supervised training in order to deal with unlabeled, limited and sparse datasets, 2) introducing prior linguistic information for regularization (e.g. thanks to a neural language model) and 3) online adaptation of the conversion model to cope with potential drift in time of the neural responses.


Requirement and Profile:


Duration: 12 months


Salary (before tax) / Month €: Depending on the experience


Starting date: Early 2020


How to apply:

Send a ​cover letter​, a ​resume​, and ​references​ by email to:

Applications will be processed as they arise.


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