20 June: FYI -- research, discourse (Nancy, FR)

Index of June 2018 | Index of year: 2018 | Full index


multilingual systems and/or transfer learning*

LORIA , team SyNaLP (Nancy,
France)


One postdoc position (1 year) in Natural Language Processing / Machine
Learning is open in the SyNaLP team (h
ttp://synalp.loria.fr/ ) at LORIA (
http://www.loria.fr/en/). This position will be funded by the LUE (Lorraine
Université d’Excellence) Future Leader program and the LORIA.


*Information*


- Starting date: as early as possible
- Duration: 1 year
- Deadline for application: open until filled
- Location: Nancy, France
- Salary: around 2,000 euros per month net income
- Informal inquiries can be sent by email to Chloé Braud (
chloe.braud@gmail.com). The application requires a brief motivation
letter and a CV.


*Topic: discourse parsing*

Documents are not just an arbitrary collection of text spans, but rather an
ordered list of structures forming a discourse. Discourse structures
describe the organization of documents in terms of discourse or rhetorical
relations (e.g. Explanation, Contrast ...) linking the semantic content of
the sentences and clauses. Discourse parsing is an integral part of
understanding information flow and argumentative structure in documents.
Building discourse parsers is currently a major challenge in Natural
Language Processing, but it’s an hard task, that involves several complex
and interacting factors, touching upon all layers of linguistic analysis,
from syntax, semantics up to pragmatics.

Previous work have focused on investigating lexico-syntactic features, with
most of the experiments on newswire data in English. The goal of this
postdoc is to investigate novel architectures for discourse parsing that
take into account different layers of analysis (e.g. syntax, co-reference,
modality, etc) and/or are able to deal with multiple languages and domains.
Another path of research would be to study the effect of discourse
information for downstream applications, such as question-answering,
summarization, sentiment analysis, etc. The aim is to explore frameworks
such as multi-task learning, to experiment with out-of-domain and
multilingual data, and to investigate representation learning for clauses,
sentences and documents.


*Requirements/qualifications*

The candidate will have to implement or modify the implementation of
existing discourse or syntactic parsers based on neural networks. S.He will
experiment with several corpora, investigating the effect of different
representations and the robustness of the chosen approach. S.He will
publish in peer-reviewed journals and conferences (ACL, EMNLP, COLING,…).


The candidate is expected to have:


- a Ph.D. or equivalent in , Computational Linguistics/NLP, Computer
Science or related fields.
- good programming skills,
- knowledge of current neural network models, and some libraries for
neural networks (e.g. Tensorflow, Keras, PyTorch, Dynet etc.),
- experience in (discourse or syntactic) parsing is a plus,
- fluent English. Knowledge of French is NOT a requirement.


Supervision of students is possible, if wanted.


*Nancy*

To learn more about living in Nancy:
https://www.nancy.fr/nancy-in-english/discover/living-in-nancy-1218.html


*Contact*

Chloé Braud , LORIA

Team SyNaLP

Email: chloe.braud@gmail.com

Index of June 2018 | Index of year: 2018 | Full index