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[Post-Doc 2020] Analysis of dialogues in psychosis or severe mental illness

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One postdoc position (1 year) in:

– Natural Language Processing / Machine Learning
OR
– Psychology

is open in the:
Semagramme team        https://team.inria.fr/semagramme/

at the:
LORIA     http://www.loria.fr/en/
Université de Lorraine, CNRS and Inria

This position will be funded by the project
OLKi – Open Language and Knowledge for Citizens
http://lue.univ-lorraine.fr/fr/open-language-and-knowledge-citizens-olki

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Pdf of the call
http://members.loria.fr/MAmblard/postdocolkicall2020/

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Information

– Starting date: fall 2020
– Duration: 1 year
– Deadline for application: The call is open while the position is available
– Location: Nancy
(https://www.nancy.fr/nancy-in-english/discover/living-in-nancy-1218.html),
France (1h30 from Paris by train)
– Salary: around 2,000 euros per month net income
– Application: CV, motivation letter, PhD evaluation, master TOR and
support letter(s) to maxime.amblard@loria.fr

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Keywords
NLP, Discourse and Dialogue, Machine Learning, corpora, Natural
Language, Pathology, Schizophrenia, Psychology

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Scientific project

Modeling interaction is a crucial step for Natural Language Processing
(NLP), which requires the development of automatic tools able to
simulate these exchanges. A typical example is chatbots and all the
services based on them. But Dialogue Models face two types of difficulties.

(I) The first issue concerns the availability of resources and models
that can analyze and process dialogues. Modeling dialogues is very
hard, in particular because conversations highlight particular uses
such as the relationship between questions and answers. Another
perspective is to use Machine Learning approaches in order to identify
dialogical relations and dialogical interactions. Generally speaking
discursive analysis aims at building a structure representing the
semantic links between sentences.

(II) The second is that dialogue models must be coordinated with
pragmatic inferences at a higher level. In this case, we can refer to
linguistic models of dialogue, or to models that capture conceptual
links, such as in TTR. While speech models provide important
information, dialogue makes it possible to share information in a
more sophisticated way. The solution must take into account the
background of all speakers, as well as how they have common ground.

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Candidate skills

The post-doctoral fellow must have either a PhD in Computational
Linguistics/NLP, Computer Science or related fields, with good
programming skills, OR in Psychology.
He/She must be fluent in English and have demonstrated its ability
to publish at the highest international level. Note that Knowledge of

French is NOT required.
Supervision of students is possible, if wanted.

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Contacts

Maxime Amblard, LORIA, Team Semagramme,
maxime.amblard@loria.fr
Chloé Braud, Irit, Team Melodi,
chloe.braud@irit.fr
Michel Musiol, ATILF, Team Discours,
michel.musiol@univ-lorraine.fr