[Eeglablist] 2 post-doc and 1 software engineer positions in Grenoble

Tue Jun 16 09:44:22 PDT 2009

 <eeglablist at sccn.ucsd.edu>Dear Colleague,

  within the context of the Open-ViBE and GAZE&EEG research projects
financed by the French National Agency of Research (ANR) we offer three
positions for autumn 2009.
All positions concern advanced applications and development of *Real-Time
Electroencephalography*.

 I would be grateful if you could diffuse the attached job offers (also see
below) in your working environment and propose them to those collaborators
of yours that could be interested and match the profiles.

Thank you very much for your attention,

Yours Sincerely,

Marco Congedo

-- 
Marco Congedo, PhD
Senior Scientist,
cnrs (Centre National de la Recherche Scientifique)
GIPSA-lab, Grenoble, FRANCE
tel +33 (0)4 76 82 62 52
http://www.lis.inpg.fr/pages_perso/congedo/MC_Home.html

*
*

*Post-doc Position in EEG Signal Processing/Machine Learning*

*for Brain-Computer Interface and Video Gaming*

* *

*Starting date*: in between October 1, 2009 and Jan 1, 2010

*Duration*: 12 months, renewable to 18 months

*Location*: GIPSA-lab, Campus Universitaire, Grenoble, FRANCE.

*Salary*: about 2,000€ net / month

*Supervision*: Marco Congedo, PhD, Senior Scientist, cnrs, marco.congedo[AT]
gmail.com

*Other collaborators at GIPSA-lab*: Christian Jutten, Bertrand Rivet, Gelu
Ionescu.

The post-doc is part of the *Open-ViBE2 project*, recently funded by the
French National researchAgency (ANR).

Brain-Computer Interface (or BCI) corresponds to the direct use of brain
signals to send “mentalcommands” to an automated system such as a robot, a
prosthesis, or a cursor on a computer screen. In the previous ANR OpenViBE1
project (Dec.2005-May2009) we have developed an open-sourceplatform to
easily design, test and use BCI (http://openvibe.inria.fr/). In addition, we
have opened new

research areas in the field of BCI, EEG signal-processing and in Virtual
Reality (VR) technologiessupporting BCI applications. This involved four
partners of the current proposal (INRIA, INSERM,GIPSA-Lab, CEA).

In OpenViBE2 we aim at adapting, in real-time and in an automated fashion,
the interaction protocolitself as well as the content of the remote/virtual
environment (VE). Our project focuses on*videogames and more particularly on
the emerging market of serious games*, which is a new field of application
for BCI. The consortium gathers partners from the leading French videogame
industry (Ubisoft, Capital-Games, Black Sheep, Kylotonn) as well as a
partner (CHArt) of the ANR project ‘LUTIN-GameLab’ that developed techniques
for gameplay assessment. In videogames, the mental

state of the user is known to be an important parameter, not to say the
ultimate target of game design.

The goal of OpenViBE2 is thus: “*exploiting EEG information to measure,
identify and use the **mental states and brain responses of the user to
adapt both the way the user can interact with the videogame and the content
of the videogame”.*

In a brain-computer interface digital signal processing algorithms for
relevant feature extraction should be fully adaptive. It is well known that
EEG task-related activities (such as focusing or movement imagination) have
a high inter-individual variability. Therefore, the feature extraction
process must adapt to the individual by means of a learning process. In a
videogame setting such learning process should be carried out seamlessly and
should not require additional efforts by the user.

The candidate will focus on optimizing digital signal processing/machine
learning strategies. The major challenge is to transpose known feature
extraction strategies in a fully on-line adaptive context, a path that has
been followed only recently in the BCI literature. New strategies will be
evaluated as well, namely, those allowing following brain dynamics in time,
space and frequency simultaneously (e.g., Hidden Markov Models).

The candidate should have a strong background in the theory of digital
signal processing and/or machine learning. He/she should have good
programming experience for coding and testing the new algorithms. Previous
experience with biomedical data and particularly with EEG or MEG and with
BCI is sought and would be a plus. The candidate will become part of a group
of researchers moved by common objectives. The candidate should possess good
knowledge of spoken and written English. The position will be filled between
October 1, 2009 and January 1, 2010. Please forward CV and names of three
recommending colleagues to the contact person (here above).

* *

*References:*

Congedo, M. (2006). Subspace Projection Filters for Real-Time Brain
Electromagnetic Imaging. IEEE Trans on Biomedical Engineering, 53(8),
1624-1634.

Congedo, M., Gouy-Pailler, C., Jutten, C. (2008). On the blind source
separation of human electroencephalogram by approximate joint
diagonalization of second order statistics. Clinical Neurophysiology, 119,
2677-2686.

Congedo, M., Lotte, F., Lécuyer, A. (2006). Classification of movement
intention by spatially filtered electromagnetic inverse solutions. Physics
in Medicine and Biology, 51, 1971-1989.

Congedo, M., Lubar, J.F. and Joffe, D. (2004). Low-resolution
electromagnetic tomography neurofeedback. IEEE Trans on Neural Systems and
Rehabilitation Engineering, 12(4), 387-97.

Sameni R., Jutten, C., Shamsollahi M. (2008) Multichannel Electrocardiogram
Decomposition Using Periodic Component Analysis, IEEE Trans on Biomedical
Engineering, 55(8), pp.1935-1940.

Sameni R., Shamsollahi M., Jutten, C. (2008) Model-based Bayesian filtering
of cardiac contaminants from biomedical recordings, Physiological
Measurement, 29(5), pp. 595-613.

Sameni R., Jutten, C., Shamsollahi M., Clifford G. (2007) A Nonlinear
Bayesian Filtering Framework for ECG Denoising, IEEE Trans on Biomedical
Engineering, 54 (12), pp. 2172-85.

Jutten C., Comon P. (Eds). Séparation de sources; Vol. 1 : Concepts de base
et analyse en

composantes indépendantes. Vol. 2 : Au-delà de l’aveugle et
applications. Lavoisier,
2007.

Jutten C., Hérault H. (1991) Blind separation of sources, part i: an
adaptative algorithm based on

neuromimetic architecture, Signal Processing, vol. 24, pp. 1–10.

Rivet B., Souloumiac A., Attina V., Gibert G.(2009). xDAWN algorithm to
enhance P300 evoked

potentials: application to brain computer interface. IEEE Trans on
Biomedical Engineering. In press.

Rivet, B., Girin, L., Jutten, C. (2007). Log-Rayleigh distribution: a simple
and efficient statistical

representation of log-spectral coefficients. IEEE Trans on Audio, Speech and
Language Processing,

15(3), 796-802.

* *

* *

*Gaze&EEG project*

At the University of Grenoble, France, for the scientific project “GAZE&EEG”
funded by the

National Research Agency, two positions are open :

· *Post-doc in EEG signal processing *(12-18 months, beginning about October
09)

· *Software or Electrical Engineer *(12 months, beginning about October 09)

* *

*Project description:*

The core of this project is the *joint processing of electroencephalogram
(EEG) and eye*

*tracking (ET) signals*, using the advanced methods of stochastic signal
processing to better

understanding the simultaneity between eye movements and neural activities.
Synchronizing

these two sources of data is essential (1) for better *denoising EEG *signals
which are contaminated by the electric activity

generated by eye movements, (2) for exploring the *functional role of eye
movements *(at the saccades and the

microsaccades level) by directly associating them to neural markers.

The context of the project is highly interdisciplinary: it involves
researchers in stochastic

signal processing, statistics, biomedical EEG signals, oculometry, visual
and textual

processing, visual perception, neuro-cognition and psycho-cognition. Several
results are

expected: (1) a technical platform for the acquisition and analysis of joint
EEG/ET recordings

to be implemented in the *Open-ViBE platform *(http://openvibe.inria.fr),
(2) new techniques

for removing EOG artifacts in EEG, (2) new method for extracting eye
micro-saccade

contributions in EEG -which is actually a very challenging issue-, (3)
scientific results on the

functional role of saccades and micro-saccades and (4) a cognitive model
able to predict an

average user scanpath on a complex document composed of text and image, in
information

searching domain.

The partners of this project are :

Grenoble , GIPSA-lab (http://www.gipsa-lab.inpg.fr/), Signal Processing and
Visualperception

Grenoble, LPNC: (http://webu2.upmf-grenoble.fr/LPNC/), Cognitive Psychology

Grenoble, TIMC : (http://www-timc.imag.fr/ ), Computer Science

LUTIN, Paris : (http://www.lutin-userlab.fr/accueil/), Cognitive Psychology

* *

*Post Doctoral position in EEG Signal Processing*

Salary: starting 2,100€ net / month depending on experience

Starting date: October 1er 2009

Duration: 12 months, renewable to 18 months

Location: GIPSA-lab, Campus Universitaire, Grenoble, FRANCE.

Contact information: Marco Congedo, Senior Scientist cnrs, GIPSA-lab,

marco.congedo[AT]gmail.com

The EEG signals are contaminated with extra-cerebral artifacts of biological
origin, and the

most energetic artifact come from eye-movements. To remove these artifacts,
the most

popular approach is the “Blind Source Separation” (BSS) based on
“Second-Order Statistics”

(SOS) or based on “Higher-Order Statistics” (HOS). These methods are in fact
sub-optimal

for the separation of eye-movements (linear model, no double dipole
modeling, etc).

Moreover, the question of the possibility to separate the miniature eye
movements

(microsaccades) has never been addressed so far. The simultaneous and
synchronous EEG/ET

recording provides an unique opportunity to remove efficiently eye-related
artefacts

exploiting the additional information provided by ET (exact position in time
with high

temporal position). The post-doc will conduct research on innovative digital
signal processing

algorithms for on-line separation and elimination of eye-movements artefact
from the EEG

based on EEG/ET recording. The developed algorithms will be implemented in
the OpenVibe

software environment (*Open-ViBE: Open platform for Virtual Brain
Environment*

http://openvibe.inria.fr/) with the aid of software engineers working within
the Open-ViBE

project. The candidate should have a strong background in theoretical
digital signal

processing and good programming experience for coding and testing the new
algorithms.

Previous experience with biomedical data and particularly with EEG or MEG
and/or ET is

sought and would be a plus. Previous experience with and knowledge of blind
source

separation will also be a plus. The candidate should be keen to work in a
team. The candidate

should possess good knowledge of spoken and written English. The position
will be filled

between October 1, 2009 and January 1, 2010. Please forward CV and names of
three

recommending colleagues to the contact person (here above).

*References:*

Congedo M., Gouy-Pailler, C., Jutten C. (2008) On the Blind Source
Separation of Human

Electroencephalogram by Approximate Joint Diagonalization of Second Order
Statistics.

Clinical Neurophysiology. doi: 10.1016/j.clinph.2008.09.007

Jutten C., Hérault H. (1991) Blind separation of sources, part i: an
adaptative algorithm based

on neuromimetic architecture,Signal Processing, vol. 24, pp. 1–10.

* *

* *

*Software or Electrical Engineer position*

Salary: starting 2,100€ net / month depending on experience

Starting date: October 1er 2009

Duration: 12 months

Location: GIPSA-lab, Campus Universitaire, Grenoble, FRANCE.

Contact information: Gelu Ionescu, Research Engeneer cnrs, GIPSA-lab,

gelu.ionescu at gipsa-lab.inpg.fr

The engineer will be responsible of developing the platform for joint EEG/ET
recordings and

to deploy it to the other partners of the project. This platform will be
developed using the

OpenVibe environment (Open-ViBE: Open platform for Virtual Brain
Environment:

http://openvibe.inria.fr/). OpenViBE is free and open source (under the term
of the L-GPL

v2+ licence). The whole software is developed in C++. It consists of a set
of software

modules that can be integrated easily and efficiently to design applications
for Brain

Computer Interfaces, neurofeedback and any other real-time EEG application
and/or for

interaction with virtual environments. Key features of the platform are
modularity reusability

and portability. The candidate should have excellent skills in C++
programming/software

development and should be keen to work in a team. Experience with EEG and/or
eye-tracking

data is a plus but not necessary. The candidate should possess good
knowledge of spoken and

written English. Position is available and should be filled October 1, 2009,
however a short

delay for starting date is possible. Please forward CV and names of three
recommending

colleagues to the contact person (here above).
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