Open position for an associate professor of Computer Science at LIPN-USPN (Paris) on Combinatorial Optimization

General profile : Computer Science
Job profile : Combinatorial Optimization
Research fields : Combinatorial Optimization

Teaching :

Department : Data Science
Location : IUT de Villetaneuse – Villetaneuse Campus
Contact : David Hébert, Head of the SD department,
Description :
The person recruited will teach at the IUT de Villetaneuse. S/he will join the Data Sciences department,
where the curriculum targets statistics and business intelligence. S/he will teach domains of computer
science related to data, such as the development of decision software, or more generally data analysis
tools, data security, etc.
According to needs, the person recruited will lecture in courses related to data science (data bases,
analysis and treatment of structured data, etc.) in the Networks and Telecommunications and
Computer Science departments.
The person recruited will also take part in the professional supervision (internships, apprenticeships),
pedagogic coordination of courses, and with time will take responsibility of a curriculum.

Research :

Laboratory : Laboratoire d’Informatique de Paris Nord (LIPN) – CNRS UMR 7030
Location : Villetaneuse campus
Contact : Frédérique Bassino, Director of LIPN,
Research team : Algorithms and Combinatorial Optimization (AOC)
Contact : Roberto Wolfler Calvo, Head of the AOC team,
Description :
The Paris-Nord Computer Science Laboratory (LIPN – CNRS UMR 7030) wishes to strengthen the
research in Combinatorial Optimization carried out by the Algorithms and Combinatorial Optimization
(AOC) team by recruiting an associate professor.

The Algorithms and Combinatorial Optimization (AOC) team includes three closely related research
axes: Polyhedron and optimization in graphs, Mathematical programming, and Distributed algorithms,
software, and architectures. The variety of approaches implemented and the wide spectrum of issues
addressed allow the team to conduct research on the theoretical and practical aspects of combinatorial
optimization and operation research, in particular by developing original methods from conception
until the implementation of the algorithms

The team has developed local collaborations (within the MathSTIC federation in particular), regional
(with CERMICS, LIX, CNAM, LAMSADE, LIP6, etc.), national (Bordeaux, Grenoble, Nantes, Nancy, etc.)
and international (Italy, USA, Mexico, Germany, Canada, Scotland, Spain, etc.). It also has numerous
industrial collaborations.

The Mathematical Programming axis of the AOC team mainly deals with the exact and approximate
resolution of combinatorial optimization problems via different approaches. Among these approaches
are cuts generation and column generation schemes, as well as decomposition and relaxation
methods. We also approach the resolution of problems by nonlinear models, polyhedral approaches,
optimization under uncertainties (reoptimization, robustness) and metaheuristics. The Polyhedron and
Optimization in Graphs axis focuses on more structural issues such as the characterization of
equimodular matrices and the description of Box-TDI systems and polyhedra. The theoretical and
methodological work is complemented by software contributions and industrial transfer.

The profile sought can come from any field of combinatorial optimization and operational research
related to one of the axes of the team.