[robotics-worldwide] [Jobs] Call for 1 PhD position on automated groups’ analysis at LTCI, Telecom ParisTech, Paris, France

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[robotics-worldwide] [Jobs] Call for 1 PhD position on automated groups’ analysis at LTCI, Telecom ParisTech, Paris, France

giovanna varni
 A PhD student opportunity is now available at LTCI, Telecom ParisTech,
Paris, France (https://urldefense.proofpoint.com/v2/url?u=https-3A__www.telecom-2Dparistech.fr_eng-2Chttps-3A__ltci&d=DwIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=vUukhgNq9gzh4LgsAtdt72CfjcrWHNVqa0M9sy9ETk8&s=29cctEEdqV7tziD78nS9xyj-wYYilKCxcVQLIwcn02Y&e=.

Groups are a fascinating interdisciplinary phenomenon. They can be defined
as bounded and structured entities that emerge from the purposive,
interdependent actions of individuals. One of the current open challenges
on automated groups’ analysis is to provide computational models of higher
level concepts called emergent states, that is states emerging as results
of affective, behavioral and cognitive interactions among the members of a
group. Cohesion is one of these states. It is a dynamic process that is
reflected in the tendency for a group to stick together and remain united
in the pursuit of its instrumental objectives and/or for the satisfaction
of members’ affective needs. Cohesion is considered as a highly valued
group property serving crucial roles for group effectiveness and
performance. Scholars proposed theoretical models of cohesion having from
one to five dimensions. Among these dimensions, the task and social ones
were the most investigated. The task dimension concerns the extent to which
group members are united to achieve the group’s goals and objectives; the
social dimension refers to the social relationships within the group (e.g.
the extent to which group members like each other). The thesis will focus
on the development of a computational model of cohesion among humans, able
to integrate its task and social dimensions and also accounting for their
relationship and their development over time.
This work will be conducted in the framework of the ANR JCJC French
national project GRACE (Groups’ Analysis for automated Cohesion

- State-of-the-art on cohesion to identify which are its most suitable and
frequent multimodal behavioral descriptors. State-of-the-art will span
several research fields, including sociology, psychology, and computer
- Computation of multimodal behavioral descriptors of cohesion
- Designing and performing experiments to collect a multimodal data set on
- Designing, implementing, and evaluating a computational model of cohesion

The ideal candidate should have a strong academic background in one or more
of the following fields: Computer Science, AI, Machine learning,
Human-Computer Interaction, Information Technology, Affective Computing,
Social Signal Processing, or closely related fields. In addition to a
passion for science and programming, you should be open to extend your
thinking to the issues linked to Human-Computer Interaction. Moreover, the
ideal candidate should have:
- Interest in multidisciplinary research at the interface between computer
science and sociology/psychology
- Excellent academic track record
- Good command of English (written and spoken)
- Strong programming skills (C++/Python)
- Very good communication skills, commitment, independent working style as
well as initiative and team spirit

Starting date: between winter 2018 and spring 2019. This is flexible and
can be negotiated with the supervisor within the above-mentioned time frame.
Application deadline: the evaluation of the PhD candidates starts
immediately and it will continue until the position is filled.
To apply please send by email to [hidden email] a
single pdf file including:
- A cover letter stating your research interests and how they could be
related to the research topic the thesis focuses on.
- A detailed CV
- Transcripts of records of your MSc
- List of at least 2 referees
- Recommendation letters

You are encouraged to contact Prof. Giovanna Varni for more information.
Please quote “PhD position” in the email subject for both asking
information and application.
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