30.1605, Support: Computational Linguistics; Psycholinguistics: PhD, Norwegian University of Science and Technology

[The LINGUIST List]

LINGUIST List: Vol-30-1605. Fri Apr 12 2019. ISSN: 1069 - 4875.

Subject: 30.1605, Support: Computational Linguistics; Psycholinguistics: PhD, Norwegian University of Science and Technology

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Date: Fri, 12 Apr 2019 12:43:19
From: Dave Kush [dave.kush at ntnu.no]
Subject: Computational Linguistics; Psycholinguistics: PhD, Norwegian University of Science and Technology, Norway

 Institution/Organization: Norwegian University of Science and Technology 
Department: Department of Language and Literature 
Web Address: https://www.ntnu.edu/ 

Level: PhD 

Duties: Research,Project Work
 
Specialty Areas: Computational Linguistics; Psycholinguistics 
 

Description:

We announce a four-year PhD position in experimental computational linguistics
at the Department of Language and Literature.

The PhD position is part of the project Computational modeling of filler-gap
acquisition in Norwegian which is an interdisciplinary project within the
Enabling Technologies strategic area at NTNU. The successful applicant will be
part of a project group headed by Associate Professor Dave Kush (Department of
Language and Literature), Professor Terje Lohndal (Department of Language and
Literature), and Professor Ole Jakob Mengshoel (Department of Computer
Science).

The project will be carried out in Kush’s ØyeLab and in cooperation with the
cross-institutional research group AcqVA (Acquisition, Variation and
Attrition) between NTNU and UiT The Arctic University of Norway. The Trondheim
unit of the group consists of 18 researchers, including 3 professors, 4
associate professors, 1 postdoc, 8 PhD candidates, and 2 20% adjunct
professors.

Job Description:
The project seeks to use computational modeling to better understand how
learners might acquire constraints on filler-gap dependencies from natural
language input. To this end, the project will evaluate whether computational
learning models of various types (e.g., Recurrent Neural Networks; Variational
Learners; Bayesian models) can (i) represent a diverse array of long-distance
filler-gap dependencies and (ii) learn the proper constraints on such
dependencies when trained on different Norwegian corpora. The results of these
investigations will be compared to previous results from English. The goal is
to ultimately identify necessary components of a learning strategy that is
capable of learning attested patterns cross-linguistically.

Applicants are requested to contact the project leader to obtain a more
detailed project description before applying.

See more information and how to apply at the application link provided below.
 

Application Deadline: 01-Jun-2019 

Mailing Address for Applications:
	Attn: Dave Kush 
	- 
	Trondheim 7491 
	Norway 
	
Web Address for Applications: https://www.jobbnorge.no/en/available-jobs/job/168456/phd-position-in-experimental-computational-linguistics 

Contact Information: 
	Dave Kush 
	dave.kush at ntnu.no  


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