32.965, Jobs: Computational Linguistics; Neurolinguistics; Psycholinguistics: Full Professor, Université de Paris

[The LINGUIST List]

LINGUIST List: Vol-32-965. Tue Mar 16 2021. ISSN: 1069 - 4875.

Subject: 32.965, Jobs: Computational Linguistics; Neurolinguistics; Psycholinguistics: Full Professor, Université de Paris

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Date: Tue, 16 Mar 2021 13:01:48
From: Benoit Crabbé [benoit.crabbe at gmail.com]
Subject: Computational Linguistics; Neurolinguistics; Psycholinguistics: Full Professor, Université de Paris, France

 
University or Organization: Université de Paris 
Department: Department of linguistics (UFRL)
Job Location: Paris, France 
Web Address: http://www.linguist.univ-paris-diderot.fr/index
Job Title: Professor
Job Rank: Full Professor

Specialty Areas: Computational Linguistics; Neurolinguistics; Psycholinguistics 


Description:

We are currently witnessing a tremendous increase in the amounts of data being
produced and/or collected by various applications and scientific disciplines.
This has been made possible with the recent advances in sensing instruments
that allow the observation of different real-world phenomena at a scale and
granularity that has never been possible, which in turn enables data-driven
scientific discovery. In other words, we are now in a position to exploit the
wealth of data to refine existing, or build new theoretical models, which
describe and explain various phenomena in the real world. 

In order to address these challenges, we need to turn our attention to a set
of new classes of Artificial Intelligence (AI), Machine Learning (ML) (both
supervised and unsupervised; including deep learning), and scalable data
analytics techniques, which produce very promising initial results. 

The candidate will have a principal affiliation to a research lab of their
main discipline, and will also be affiliated to the Data Intelligence
Institute of Paris (diiP). The candidate will have recognized research work
and convincing interest in interdisciplinary work, for developing novel
methods in the intersection of AI/ML/statistical learning/data analytics/data
intelligence that address fundamental challenges in modern science, industry,
and society.

Below you find the profile for a candidate in Linguistics; candidates with
other profiles that fit the perspective discussed above in particular within
the fields of Particle, or Astroparticle Physics and Astronomy or Computer
Science will be examined for this position.

Linguistics traditionally makes the fundamental hypothesis that language has
structure, in particular that sentences are recursively structured as trees.
Some of the structural constraints have been claimed to underlie all human
languages and not to be learnable. However, the recent emergence of deep
learning and unsupervised methods, such as recurrent networks and
transformers, provide new models, hypotheses and research directions that can
be confronted with such approaches and may allow a deeper understanding of
natural languages. The selected candidate will have a proven research program
designing, analyzing and interpreting such models based on large corpora
and/or experimental data (Eye Tracking, EEG, NIRS, fMRI) combining theory and
experimentation and taking the diversity of languages into account. He or she
is expected to have significant expertise in current research directions both
in linguistics and in data science.

Teaching:
Depending on the profile of the successful candidate, teaching will take place
in one or more relevant departments, at both the undergraduate and graduate
levels. Moreover, in collaboration with diiP, the candidate will propose
graduate courses on data analytics/intelligence that could be relevant to
students from different research fields and disciplines. 

Teaching in linguistics concerns: 
- Master Linguistique Théorique et Expérimentale
- Master Linguistique Informatique
- Master in Information Technology

The position is published on the French Galaxie site
(https://galaxie.enseignementsup-recherche.gouv.fr/antares/fichePosteFidis?tel
echarger=Telecharger&profil=eta&numemp=154&numetab=0755976N).

Applications have to be performed online from the Galaxie web site.

Applicants are strongly advised to contact Barbara Hemforth at the contact
information provided below.



Application Deadline: 23-Apr-2021 
	  
Web Address for Applications: https://www.galaxie.enseignementsup-recherche.gouv.fr/ensup/cand_recrutement.htm 
Contact Information:
	Mrs Barbara Hemforth 
	Email: barbara.hemforth at linguist.univ-paris-diderot.fr 


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