Call for post-doc applications in Natural Language Processing for
scientometrics (Grenoble Alps University, France)

Starting date:  January. 03, 2022 at the earliest
Duration:         full-time position for 24 months (with a possibility of reappointment)
Salary:             according to experience (up to 4142¤ / month)
Deadline:         Nov 30th, 2021
Location:          The position will be based in Grenoble, France. Remote work is partly possible (e.g., 1 day a week).
Keywords:        natural language processing, citation classification, citation content/context analysis, scientometrics, name entity recognition, argument mining, transfer learning, deep learning

*Context*

The Grenoble Alps University has an open position for a highly
motivated postdoc researcher. The successful candidate will work on
the multi-disciplinary ERC Synergy research project NanoBubbles
(https://nanobubbles.hypotheses.org) supported by the European
Research Council (ERC). The project objective is to understand how,
when and why science fails to correct itself. The project's focus is
claims made within the field of nanobiology. Project members combine
approaches from the natural sciences, computer science, and the social
sciences and humanities (Science and Technology Studies) to understand
how error correction in science works and what obstacles it faces. For
this purpose, we aim to trace claims and corrections in various
channels of scientific communication (journals, social media,
advertisements, conference programs, etc.) via natural language
processing (NLP) techniques.

*Main tasks*

The challenge is to build datasets, models and tools that enable
analysing how scientific papers are cited, how claims appear in
scientific records and are propagated. This challenge also encompasses
the analysis of the rapidly evolving ecology of on-line comments (on
post-publication peer-review venues, for instance) complementary to
conventional scientific records. The project is interested in hiring
people able to contribute to one or more of the following challenges:


- Leveraging existing and developing new NLP methods to retrieve
  citation contexts, detect citation polarity and build citation
  network of scientific statements. This means not only counting
  citations received by a publication but also assessing the content
  of both cited and citing documents, whether the citation occurs in a
  scientific paper, a tweet or an on-line comment.

- Leveraging existing and developing new NLP methods to detect, track
  and identify named entities, claims and counterclaims in scientific
  publications and social media.

- Take advantage of existing corpus to learn models but also build
  tools for creation and annotation of new datasets so as to visualise
  the propagation of claims and counterclaims.


The hired person will interact with PhD students, interns and
researchers hired as part of the ERC project. According to his/her
background he/she will work in on one or more of the above-mentioned
challenges. The hired post-doc would also be expected to lead the
diffusion of corpus collected through open source platforms and/or
open shared tasks organisation.


*Scientific environment*

The person recruited will be hosted within the Sigma and Getalp teams
of the LIG laboratory (http://sigma.imag.fr/ and
https://lig-getalp.imag.fr/), which offers a dynamic, international,
and stimulating framework for conducting high-level multi-disciplinary
research. The teams are housed in a modern building (IMAG) located in
a 175-hectare landscaped campus that was ranked as the eighth most
beautiful campus in Europe by Times Higher Education magazine in 2018.

The person will also be required to collaborate with several teams
involved in the ERC Nanobubbles project, in particular with
researchers in France from the IRIT lab (Toulouse, France), Ecole des
Ponts ParisTech, University of Sorbonne Paris-Nord, CNRS, as well as
researchers from in the Netherlands including Maastricht University,
Radboud Universiteit and University of Twente.


*Requirements*

The ideal candidate must have a PhD degree in Natural Language
Processing, computer science.

The successful candidate should have:

· Good knowledge of machine learning techniques
· Good knowledge of Natural Language Processing, previous experience
       in NER, RE.
·      Experience in corpus collection/formatting and manipulation.
·      Strong programming skills in Python
·      Excellent publication record
·      Willing to work in multi-disciplinary and international teams
·      Good communication skills

*Instructions for applying*

Applications are expected until Nov 30th, 2021 and must be addressed
to Cyril Labbé (cyril.labbe@imag.fr), François Portet
(Francois.Portet@imag.fr), Frédérique Bordignon
(frederique.bordignon@enpc.fr).

Applications will be considered on the fly. It is therefore advisable
to apply as soon as possible. The application file should contain:


· Curriculum vitae

· References for potential letter(s) of recommendation

· One-page summary of research background and interests

· At least three publications demonstrating expertise in the
       aforementioned areas

· Pre-defence reports and defence minutes; or summary of the thesis
       with date of defence for those currently in doctoral studies