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CHI-ANNOUNCEMENTS  September 2018, Week 4

CHI-ANNOUNCEMENTS September 2018, Week 4

Subject:

Two-year Post-doc. Position - Multimodal Data Processing, Aix Marseille University, France

From:

Magalie Ochs <[log in to unmask]>

Reply-To:

Magalie Ochs <[log in to unmask]>

Date:

Wed, 26 Sep 2018 16:48:23 +0200

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (107 lines)

*
*

*Two-year Post-doctoral Position
*

*
*
/

/Multimodal data analysis of behavioral and physiological signals from 
human-human and human-machine interactions/

/
/
*deadline for application : 30 October*
/

/Laboratoire d’Informatique et des Systèmes (LIS) et Laboratoire Parole 
et Langage (LPL) /

Aix-Marseille Université & CNRS

*_Keywords:_* conversational speech, multimodal data analysis, 
neurophysiological data, machine learning

The A*MIDEX project /PhysSocial/ aims at a betterunderstanding of the 
specificities of social interactions by comparing relationships between 
behavior and neurophysiologyin human‐human and human‐robot discussion. 
The goal of the post-doc is toanalyze the multimodal signals (speech, 
eyes direction, physiological, and neurophysiologic signals) from 
conversational activity using signal processing and machine learning 
methodologies in order to compare the human-human and human-robot 
interactions.

The Post-doc is organized around 2 main tasks:

  * /Multimodal data preprocessing/: in a first step, the objective is
    to process the row data (speech, transcribed speech, eyes tracking,
    physiological and neurophysiological signals) corresponding to
    human-human and human-robot conversation in order to extract time
    series corresponding to behavioral features, as well as cognitive
    events derived from local activity in well-defined brain areas
    involved inlanguage and social cognition
  * /Machine learning of causal relations: /in a second step,//time
    series will be used by statistical learning to identify causal
    relations between behavioral and physiological features and
    cognitive events extracted from neurophysiological recording with
    fMRI. From a learning point of view, one challenge in this project
    is the high-dimensional data. We address this issue with a focus on
    the features representation and selection problems.

The candidate should have a Phd in Computer Science, Applied 
Mathematics, Signal or Natural Language Processing (with solid 
background in machine learning).

The candidate should have a strong background in machine learning and 
signal processing with a focus on multimodality. Some complementary 
previous experience would be appreciated in the following topics:
• Multimodal data processing
• Data science applied to language data


The post-doc is fully funded during 2 years as part of the A*MIDEX 
interdisciplinary project PhysSocial, including personalized training, 
travel expenses, and conferences attendance.

French language is not required.

Aix Marseille University (http://www.univ-amu.fr/en), the largest French 
University, is ideally located on the Mediterranean coast, and only 1h30 
away from the Alps.


The application files consists of the following documents:
- A detailed curriculum with publications,
- A description of Phd subject,
- A description of the academic background and copy of academic records 
and most recent diploma,
- 2 recommendation letters (including one from the Phd supervisor)


The application files should be sent to :
Laurent Prévot: [log in to unmask] 
<mailto:[log in to unmask]>
and
Magalie Ochs: [log in to unmask] <mailto:[log in to unmask]>

For any question, contact :

Laurent Prévot: [log in to unmask] 
<mailto:[log in to unmask]>
www.lpl-aix.fr/person/*prevot* <http://www.lpl-aix.fr/person/*prevot*>

Magalie Ochs: [log in to unmask] <mailto:[log in to unmask]>
http://www.lsis.org/ochsm/

    ---------------------------------------------------------------
    For news of CHI books, courses & software, join CHI-RESOURCES
     mailto: [log in to unmask]

    To unsubscribe from CHI-ANNOUNCEMENTS send an email to
     mailto:[log in to unmask]

    For further details of CHI lists see http://listserv.acm.org
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