Job: Post-doc: Multimodal data analysis of behavioral and physiological signals from HHI, HMI interactions – Aix Marseille University

Two-year Post-doctoral Position

Multimodal data analysis of behavioral and physiological signals from human-human and human-machine interactions
Laboratoire d’Informatique et des Systèmes (LIS) et Laboratoire Parole et Langage (LPL)
Aix-Marseille Université & CNRS
France

Deadline for application: 30 October

Keywords: conversational speech, multimodal data analysis, neurophysiological data, machine learning

The A*MIDEX project PhysSocial aims at a better understanding of the specificities of social interactions by comparing relationships between behavior and neurophysiology in human‐human and human‐robot discussion. The goal of the post-doc is to analyze 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 in language 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: laurent.prevot@univ-amu.fr
and
Magalie Ochs: magalie.ochs@lis-lab.fr

For any question, contact:

Laurent Prévot: laurent.prevot@univ-amu.fr
www.lpl-aix.fr/person/*prevot*

Magalie Ochs: magalie.ochs@lis-lab.fr
http://www.lsis.org/ochsm/

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