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"ACM SIGCHI General Interest Announcements (Mailing List)" <[log in to unmask]>
Wed, 26 Sep 2018 16:48:23 +0200
Magalie Ochs <[log in to unmask]>
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Magalie Ochs <[log in to unmask]>
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*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 

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 (, 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]>
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]>*prevot* <*prevot*>

Magalie Ochs: [log in to unmask] <mailto:[log in to unmask]>

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