Could you please distribute the following job offer? Thanks.
Best,
Pascal
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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
(pascal.denis@inria.fr).
The starting date of the position is 1 November 2022 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/