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11 juillet 2018

PhD opening in Machine learning for Neural Encoding of Naturalistic Auditory Scenes - IMT Atlantique and Université de Montréal

Catégorie : Doctorant

We invite applications for a fully-funded PhD between Universite de Montreal, computer science department, and IMT Atlantique, Brest, France.
The goal is to model the perception of complex natural auditory stimuli using signals on dynamic brain graphs, and deep learning.

Details are here : https://t.co/963vd9Pizg and below

Deadline for application is July 25th.


The project aims to model natural auditory perception using artificial
neural networks and graph signal processing, applied to human functional
magnetic resonance imaging (fMRI) and electroencephalograph (EEG) data.
Recent advances in artificial intelligence are largely due to the
outstanding performance obtained by deep neural networks on the
classification of composite natural stimuli. Deep learning however still
faces important challenges with natural auditory perception [1], in
particular in complex, noisy scenes involving several simultaneous sources.
This thesis will use human neuroimaging data to improve the ability of
artificial networks to classify natural auditory stimuli.

Recent works have demonstrated the feasibility of building artificial
models to link computational musical features with brain activity [2]. Such
models perform as well as human listeners on both music, and simple speech
discrimination tasks [3]. The internal layers of the deep networks have
also been used to predict brain activity related to natural sounds, by
modeling each individual voxel of fMRI activity using combinations of
feature maps [3]. We propose to investigate extensions of the current
approaches to consider graph convolutional networks [4], signal processing
on graphs [5], and to model temporal signals on dynamic graphs [6]. We will
build a series of artificial models, using extensive recordings of EEG/fMRI
brain activity acquired from participants performing auditory tasks of
increasing complexity.

This PhD project is a collaboration between the laboratories of Dr. Nicolas
Farrugia and Dr Vincent Gripon (Brain Inspired Artificial Intelligence
Project, at IMT Atlantique, Brest, France), and the lab of Dr. Pierre
Bellec (NeuroMod - Courtois Project on Neuronal Modelling - CRIUGM,
Department of Computer Science and Operational Research, Universit? de
Montr?al, Montr?al, Qc, Canada). The candidate will be expected to share
their time between Montreal and Brest. IMT Atlantique is a public
technological university focusing on the training of engineers at the MSc.
level and junior researchers at the PhD level. Universit? de Montr?al is a
world-renowned institution, training elite scientist, and is currently one
of the main hubs for artificial intelligence and neuroinformatics research
in North America.

Candidate profile

• Master’s degree in machine learning or computer science or biomedical imaging or signal / image processing or auditory perception / psychoacoustics, or Neurosciences.

• Basic knowledge of machine learning algorithms

• Solid programming skills

• At least one of: experience in experimental design, research experience in deep learning / machine learning of large datasets, research experience related to auditory or musical perception, laboratory experience in EEG or fMRI testing of human subjects.


To apply (deadline July 25th) :

Send an email to nicolas.farrugia@imt-atlantique.fr and pierre.bellec@criugm.qc.ca with the following:

• a full curriculum vitæ

• recommendation letters or contacts from former teachers/advisors

• a cover letter stating your motivation and fit for this project

• Full university transcripts

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(c) GdR 720 ISIS - CNRS - 2011-2018.