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Master in Science of Complex Systems

To candidate to the program, please follow the instructions underneath.

The “Complex Systems” master training, with emphasis on “Physics, Computer science and Complex Networks”, is an option of Master 2 that is part of the Masters of Physics (Sciences de la Matière / Parcous Science et Innovation), the Master of Biology (Biosciences), and the lectures are also accessible for the students in the Master of Computer Science (Informatique Fondamentale), Masters organised by the ENS of Lyon and University Lyon 1, so as to provide an innovative training for students who are interested in the interdisciplinary research of complex networks and modeling of complex systems.

This program maintains a balance between different disciplines by combining courses from the fields of biology, computer science, mathematics, physics and sociology. Students from all of these disciplines are welcome to participate; the student will follow both the ”Complex Systems” program and part of their own M2: Computer Science, Physics, or Bioscience (please contact the people responsible of the program for more details).

The inscriptions to the program has to be made by following the procedure of the ENS de Lyon webpage : Follow the online procedure for admission in Master et the ENS of Lyon (or the University of Lyon 1). For the ENS of Lyon, this is explained here in french (for student already in France) or here: admission at ENS de Lyon (in english) for others. Be attentive to the deadlines. Also, please contact Pierre Borgnat, currently in charge this part of Master, so that we are aware of the application. 

The program puts a special focus on the theory and modelling of complex networks and provides special training in data-driven research. In the end of the program students will receive a degree supplement assigned in their original master degree. All courses are given in English (optionally in French if all the students are fluent in French) for 4 or 6 ECTS during the fall between September and February. For a successful validation the participating students are required to collect 30 ECTS during the first semester, and 30 ECTS for the second semester, from the following offer:

Mandatory courses

  • Introduction to Computer Science  (P. Koiran) ; 20h + 8h TD; 6 ECTS  (*)
  • Epistemology of the modeling of complex systems (S. Franceschelli) ; 8h
  • Complex Networks, (R. Cazabet, L. Pacini) ; 24h + 6h TD, 4 ECTS
  • Methods in Complex Systems, (T. Nguyen-Huu, N. Garnier) ; 18h + 6h TD, 3 ECTS

(* : these lectures can not be taken by students from Computer Science Master)

Research courses

  • Data analysis and processing for networks, P. Borgnat, P Abry, S. Roux - 18h, 3 ECTS
  • Machine learning, N. Pustelnik, P. Abry, P. Borgnat, 18h, 3 ECTS, 
  • Modeling in biology and médecine, L. Pujo-Menjouet, B. Audit, O. Gandrillon - 18h, 3ECTS
  • Modeling of Social Systems, P. Jensen - 18h, 3ECTS
  • Other research lectures in Master 2 in Computer Science Master or Physics (or other Masters)

Research Internship

The students have to follow a research internship of at least 16 or 20 weeks, during the second semester and it will count as 18 or 30 ECTS (validated by a written report and an oral presentation).


For further details about the program please contact the people in charge:

Schedule of 2020-2021

Beginning of lectures of the first semester: early September 2020. End of 1st semester: 1st week of January 2021. Second semester: Research internship up to mid July 2021.

See the schedule of 2020-2021 here:

Link to the schedule of the specific lectures in Complex Systems



ENS Lyon provides different scholarship programs for international students:

For further details please visit the site of the international student office of ENS Lyon. ERASMUS students from universities with partnership agreement with ENS Lyon are welcome.

Nov 06, 2020
Nov 06, 2020 Bravo aux 3 lauréats du Prix de Thèse Systèmes Complexes 2020 : Anass El Aouni, Samuel Nordmann et Odile Plattard pour leurs contributions originales !
Aug 25, 2020 Spatial and temporal regularization to estimate COVID-19 reproduction number R(t): Promoting piecewise smoothness via convex optimization. journal.pone.0237901
Jun 18, 2020 * Date limite (prolongation) : les propositions devront être soumises au plus tard le mardi 23 juin 2020 à 23h59 * Détails : * Les propositions sont à soumettre sur le site easychair :