Hi there, 

Could you please distribute the following job offer? Thanks. 

Best, 

Pascal 

> -------------------------------------------------------------------------------------

> We invite applications for a 3-year PhD position co-funded by Inria,
> the French national research institute in Computer Science and Applied
> Mathematics, and LexisNexis France, leader of legal information in
> France and subsidiary of the RELX Group.

> The overall objective of this project is to develop an automated
> system for detecting argumentation structures in French legal
> decisions, using recent machine learning-based approaches (i.e. deep
> learning approaches). In the general case, these structures take the
> form of a directed labeled graph, whose nodes are the elements of the
> text (propositions or groups of propositions, not necessarily
> contiguous) which serve as components of the argument, and edges are
> relations that signal the argumentative connection between them (e.g.,
> support, offensive). By revealing the argumentation structure behind
> legal decisions, such a system will provide a crucial milestone
> towards their detailed understanding, their use by legal
> professionals, and above all contributes to greater transparency of
> justice.

> The main challenges and milestones of this project start with the
> creation and release of a large-scale dataset of French legal
> decisions annotated with argumentation structures. To minimize the
> manual annotation effort, we will resort to semi-supervised and
> transfer learning techniques to leverage existing argument mining
> corpora, such as the European Court of Human Rights (ECHR) corpus, as
> well as annotations already started by LexisNexis. Another promising
> research direction, which is likely to improve over state-of-the-art
> approaches, is to better model the dependencies between the different
> sub-tasks (argument span detection, argument typing, etc.) instead of
> learning these tasks independently. A third research avenue is to find
> innovative ways to inject the domain knowledge (in particular the rich
> legal ontology developed by LexisNexis) to enrich enrich the
> representations used in these models. Finally, we would like to take
> advantage of other discourse structures, such as coreference and
> rhetorical relations, conceived as auxiliary tasks in a multi-tasking
> architecture.

> The successful candidate holds a Master's degree in computational
> linguistics, natural language processing, machine learning, ideally
> with prior experience in legal document processing and discourse
> processing. Furthermore, the candidate will provide strong programming
> skills, expertise in machine learning approaches and is eager to work
> at the interplay between academia and industry.

> The position is affiliated with the MAGNET [1], a research group at
> Inria, Lille, which has expertise in Machine Learning and Natural
> Language Processing, in particular Discourse Processing. The PhD
> student will also work in close collaboration with the R&D team at
> LexisNexis France, who will provide their expertise in the legal
> domain and the data they have collected.

> Applications will be considered until the position is filled. However,
> you are encouraged to apply early as we shall start processing the
> applications as and when they are received. Applications, written in
> English or French, should include a brief cover letter with research
> interests and vision, a CV (including your contact address, work
> experience, publications), and contact information for at least 2
> referees. Applications (and questions) should be sent to Pascal Denis
> ([email protected]) and Damien Sileo ( [ mailto:[email protected] |
> [email protected] ] ).

> The starting date of the position is 1 September 2023 or soon
> thereafter, for a total of 3 full years.

> Best regards,

> Pascal Denis

> [1] https://team.inria.fr/magnet/
> [2] https://www.lexisnexis.fr/

> --
> Pascal

> ----
> Pour une évaluation indépendante, transparente et rigoureuse !
> Je soutiens la Commission d'Évaluation de l'Inria.
> ----

> +++++++++++++++++++++++++++++++++++++++++++++++
> Pascal Denis
> Equipe MAGNET, INRIA Lille Nord Europe
> Bâtiment B, Avenue Heloïse
> Parc scientifique de la Haute Borne
> 59650 Villeneuve d'Ascq
> Tel: ++33 3 59 35 87 24
> Url: http://researchers.lille.inria.fr/~pdenis/
> +++++++++++++++++++++++++++++++++++++++++++++++
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