Master's degree in Modelling, Data Analysis and Scientific Computing (MADOCS) Director: Bernard.Chalmond @ u-cergy.fr

The Master's degree in Modelling, Data Analysis and Scientific Computing (the initials in French giving "MADOCS") has three majors, which may be combined in various proportions: 

 TI for Information Processing ( Coordination: Dominique.Laurent @ u-cergy.fr )
 VS for Scientific Vision ( Coordination: Armen.Shirikyan @ u-cergy.fr )
 CS for Scientific Computing ( Coordination: Francois.Dunlop @ u-cergy.fr )

Job outlook
R&D engineer, with competence in :
 scientific programming (C, Java, SAS, Matlab, data bases, algorithmics) ;
 computational techniques for modelling and simulation (optimisation, CAD, finite elements, Monte Carlo, dynamical systems) ;
 modelisation and processing of data (data warehousing, data mining, etc) ;
 interpretation of physical phenomena (fluid mechanics, structural mechanics, electromagnetism, sismology).

Jobs will be found in research departments and design offices in the industry, and also in consulting firms.

Admission
Into M1 (first year) : from a three-year Bachelor's degree in maths, physics or computer science.
Into M2 : from M1-MADOCS or by dossier+interview from 4-year university or engineering school education, with a curriculum including maths, physics and/or computer science.

Research laboratories (on campus)
 Analyse, géométrie et modélisation - AGM (UMR 8088)
 Laboratoire de physique théorique et modélisation - LPTM (UMR 8089)
 Équipes traitement de l’image et du signal - ETIS (UMR CNRS 8051/UCP/ENSEA)

Partner Engineering School: École Internationale des Sciences de Traitement de l’Information

Former students

M2 (60 ECTS)	Information processing	Scientific Vision	Scientific computing
S3 (30 ECTS)	S3	S3	S3
Core courses (15 ECTS)	Geometric modelisation  Statistical learning II  Finite elements  Inverse problems  Computational fluid dynamics II	Geometric modelisation  Statistical learning II  Finite elements  Inverse problems  Computational fluid dynamics II	Geometric modelisation  Statistical learning II  Finite elements  Inverse problems  Computational fluid dynamics II
Choice courses (15 ECTS)	Data warehousing  Data mining  Parallel and distributed computing  Simulation for networks and distrubuted systems  Stochastic processes	- Image modelisation  Computer graphics  Virtual reality  CAO  Multi-scale representation	- Geophysics  Civil engineering  Electrical engineering   Medical and industrial imaging  Finite elements II
S4 (30 ECTS)	S4	S4	S4
Core courses (9 ECTS)	Monte-Carlo techniques  Management and communication	Monte-Carlo techniques  Management and communication	Monte-Carlo techniques  Management and communication
Internship + English : 5-6 months (18 + 3 ECTS)	Industrial or academic  English (TOIC + internship presentation in English)	Industrial or academic  English (TOIC + internship presentation in English)	Industrial or academic  English (TOIC + internship presentation in English)