Teaching: Computer Science department – IUT Villetaneuse
Research: RCLN and/or AOC teams
Website for applying:
https://www.galaxie.enseignementsup-recherche.gouv.fr/ensup/cand_recrutement_enseignants_chercheurs.htm
Description
Teaching
Computer Science Department
Address:
IUT de Villetaneuse – Université Sorbonne Paris Nord
Job description:
The successful candidate will teach computer science in BUT (Bachelor Universitaire de Technologie) in the computer science department of the IUT of Sorbonne Paris Nord University.
The teaching content follows a national educational program of IUT.
Database skills will be particularly appreciated. The needs relate to the creation and querying of databases; the design of a database; introduction to the SQL language and advanced SQL programming; the introduction of approaches beyond relational (noSQL) and the quality of a database.
The successful candidate is expected to participate and invest in the collective life of the department. In particular, in the short/medium term, the lecturer will be asked to participate in the organization of SAEs (SAé – Learning and Evaluation Situations) and other teaching responsibilities.
Contacts:
First and last name: Aomar Osmani
Email: aomar.osmani@univ-paris13.fr
First and last name: Franck Butelle
Email: Franck.Butelle@univ-paris13.fr
Research
Research Unit:
Laboratoire d’Informatique de Paris Nord (UMR CNRS 7030)
Description:
The Laboratoire d’Informatique de Paris-Nord (LIPN – CNRS UMR 7030) is seeking to recruit a Maître.sse de Conférences to strengthen research in either of the following two teams: Algorithms and Combinatorial Optimization (AOC) or Knowledge Representation and Natural Language (RCLN).
- The AOC team tackles issues ranging from the theory to the practice of combinatorial optimization and operations research. It studies combinatorial problem structures and develops solution approaches based on polyhedra, graph optimization and mathematical programming. It is also interested in the implementation of these algorithms for industrial applications. The team has developed local, regional, national and international collaborations. It also has numerous industrial collaborations.
The profile sought by the AOC team may come from any field of combinatorial optimization and operations research related to the team’s research themes. A profile with an interest in linear and non-linear optimization, polyhedra or decomposition methods will be particularly appreciated. Additional expertise in topics such as optimization under uncertainty, problem complexity, learning for optimization, decision theory or graph theory will also be welcome. - The RCLN team brings together skills in Automatic Language Processing, corpus linguistics, knowledge graphs as well as data mining and machine learning. These complementary skills enable us to innovative work in text corpus analysis (Axis 1) and exploration (Axis 2), as well as in knowledge acquisition using from knowledge graphs or texts (Axis 3). The approaches developed enable us to deal with complex problems in texts or knowledge graphs, such as deep syntactic analysis, simultaneous extraction of semantic relations and semantic relations and named entities, or graph completion, using methods derived from deep learning optimization and graph mining. The team plays an active role in the direction and work of the LabEx “Empirical Foundations of Linguistics”.
The team is looking for a profile capable of integrating into one of its research axes.
Web site:
RCLN team: https://lipn.univ-paris13.fr/rcln/
AOC team: https://lipn.univ-paris13.fr/aoc/
Contacts :
Frédérique Bassino
LIPN Director
frederique.bassino@univ-paris13.fr
Nathalie Pernelle
Head of RCLN team
pernelle@lipn.univ-paris13.fr
Roberto Wolfler Calvo
Head of AOC team
wolfler@lipn.univ-paris13.fr