Target level
Baccalaureate +5
ECTS
120 credits
Duration
2 years
Component
UFR IM2AG (informatique, mathématiques et mathématiques appliquées), UFR Sciences de l'Homme et de la Société (SHS), Grenoble INP - Ensimag (Informatique, mathématiques appliquées et télécommunications), UGA
Language(s) of instruction
English, French
Presentation
Below is a diagram (in French) of the structure of the master : on the left column, the first year masters (core curriculum), on the center and right columns the second year masters.
Co-accredited training between the Grenoble Alpes University, the Polytechnic Institute of Grenoble, and the University of Savoie Mont-Blanc.
This master courses offers several programs :
- Science industrial applied mathematics (MSIAM) : first year + second year
- Preparation for agregation : second year
- Cybersecurity (CybSec) : second year
- Fondamental mathematics : second year
- Statistics and data science (1) : first year + second year
- Operation recherch combinatorics and optimization (ORCO) : second year
- Mathematical modeling applied analysis (MMAA) (2) : first year + second year
(1) Co-delivered by the Humanities and social sciences teaching department of Grenoble Alpes University
(2) Delivered by the Université de Savoie Mont Blanc
The master proposes two core curricula :
- General mathematics core curriculum in French
- Applied mathematics core curriculum in French and English
Differentiation at first year level : The optional teaching units proposed in semester 7 and semester 8 aim at guiding the students towards the various courses of the second year of the master. The Statistics and data science program is independent of the core curricula. The Mathematical modelling applied analysis program is also independent of the core curricula, but one can enter it at the second year level.
Differentiation of the courses at the second year level (Statistics and data sciences and Mathematical modelling applied analysis excepted) :
- The Science in industrial and applied mathematics, based on the core curriculum Applied mathematics accessible via the core curriculum General mathematics
- Fundamental mathematics, based on the core curriculum General mathematics
- Preparation for agregation, based on the core curriculum General mathematics
- Cybersecurity, accessible via the core curricula Applied mathematics and General mathematics, as well as via the core curriculum Computer science of the Computer science master program
- ORCO, accessible via the core curricula Applied mathematics and General mathematics, as well as via the core curriculum Computer science of the master program Computer science
The objective of this master is to train highly skilled specialists in mathematics and computer science for engineering, teaching, and research in a wide range of fields (pure and applied maths) where the demand from the socio-economic world is strong : security and cryptology, scientific computing, operational research, big data analysis, image synthesis and processing, statistics...
Identifier ROME
IT studies and development
Skills
The basic courses (between 40 and 50 ECTS) are offered in French or English in the first year of the Master.
For research-oriented courses: body of general research-related competencies
- formulate a problem, establish a state of the art, estimate the feasibility, and the impact of a resolution of problem, establish, follow a strategy. Skills are acquired during TER, projects and internships research in M1 and M2 (> 30 ECTS).
Discovery of the socio-economic world offered to all students through introductory modules to the company, project and industrial internships (at least 36 ECTS for career paths), the business forum (presentation of ~ 40 companies, interviews, tables rounds ...) and thematic conferences given by industry.
All students also have access to language courses (English or French as a foreign language depending on their level, 6 ECTS)
International education
- Double degrees, joint degrees, Erasmus Mundus
- Education with formalized international partnerships
- Internationally-oriented programmes
International dimension
- Course CM-BHC in Erasmus Mundus
- CS course, MSIAM are entirely in English, international recruitment
- MF course taught in English according to the public, international recruitment
Organisation
Abroad intership
In France or abroad
Program
Select a program
Preparation for agregation
To view the presentation of the Preparation for agregation program in French click on the following link : Préparation à l'agrégation
Fundamentals mathematics
This is a high-level training in fundamental mathematics research. This course is the gateway to contemporary research in fundamental mathematics, in Grenoble. The master 2nd year honors in Mathematics and mathematical applications pathways of the Fourier institute is part of the Graduate school of mathematics, Information sciences and technologies, Computer science and depends on the University Grenoble Alpes. This course is recommended to students from the 1st year of general mathematics, and candidates to the agregation of mathematics, before they perform their tenure.
The objectives are to have an ntroduction to fundamental mathematics research. Preparation for a PhD thesis.
UE Algebra
9 creditsUE Holomorphic functions
6 creditsUE Probabilities
9 creditsUE Analysis
9 credits
UE Study and research work
6 creditsOptional
UE Effective algebra and cryptographie
6 creditsUE Compléments sur les EDP
6 creditsUE Differential geometry
6 creditsUE Markov process
6 creditsUE Galois theory
6 creditsUE Operations Research (AM)
6 credits
Choice: 1 among 2
UE English S8
3 creditsUE Opening UE (only if C1 level in English reached)
3 credits
Choice: 2 among 3
UE Morse theory in geometry and topology
12 creditsUE Random models on lattices
12 creditsUE Analysis and probability on manifolds
12 credits
Choice: 1 among 2
UE Research internship
27 creditsUE English
Operations Research, combinatorics and optimization (ORCO)
Semester 9 corresponds to the specialization training and semester 10 consists of a practicum in a company or laboratory of 5 to 7 months, which represents 30 European Credit Transfer and Accumulation System credits. The master in Operations research, combinatorics and optimization is one of the possible specializations for the second year of the master of science in Computer science. The courses are taught in English.
The scientific objectives are :
- To train students in the foundations and methods of operational research (mathematical programming, graph theory, complexity, stochastic programming, heuristics, approximation algorithms...)
- To prepare students to use and develop these methods to solve complex industrial applications (supply chain, scheduling, transport, revenue management, etc.) and implement the corresponding software solutions
Students leaving this course equipped to, according to their preferences, move towards the research professions (academic or industrial thesis), enter, as a specialist engineer, major research and development departments in optimization (SNCF, IBM, Air France, Amadeus etc) or enter optimization consulting firms (Eurodécision, Artelys...). They will also be able to enter less specialized companies by highlighting their ability to methodologically analyse operational problems, thus demonstrating that they are potential key elements in the improvement of the company's performance (by linking up with specialized firms or developing in-house methods).
In the longer term, students who are oriented towards the industrial world should be able, with their experience in improving company performance and good "business" knowledge, to naturally access decision-making positions at high levels of responsibility.
The course is labelled "Core AI" by MIAI.
UE Object-oriented and software design
3 creditsUE Partial differential equations and numerical methods
6 creditsUE Signal and image processing
6 creditsUE Geometric modelling
6 creditsUE English
3 creditsUE Applied probability and statistics
6 creditsUE Systèmes dynamiques
3 creditsUE Instability and Turbulences
3 creditsUE Turbulence
3 credits
UE Computing science for big data and HPC
6 creditsHPC
Introduction to database
3 credits
UE Project
3 creditsUE Internship
3 creditsUE Numerical optimisation
6 creditsChoice: 2 among 6
UE Operations Research (AM)
6 creditsUE Introduction to cryptology (AM)
6 creditsUE 3D Graphics (AM)
6 creditsUE Turbulences
6 creditsUE Statistical analysis and document mining
6 creditsUE Variational methods applied to modelling
6 credits
UE Object-oriented and software design
3 creditsUE Partial differential equations and numerical methods
6 creditsUE Signal and image processing
6 creditsUE Geometric modelling
6 creditsUE Applied probability and statistics
6 creditsUE English
3 credits
UE Computing science for big data and HPC
6 creditsHPC
Introduction to database
3 credits
UE Project
3 creditsUE Internship
3 creditsUE Numerical optimisation
6 creditsUE GS_MSTIC_Scientific approach
6 creditsChoice: 1 among 6
UE Operations Research (AM)
6 creditsUE Introduction to cryptology (AM)
6 creditsUE 3D Graphics (AM)
6 creditsUE Turbulences
6 creditsUE Variational methods applied to modelling
6 creditsUE Statistical analysis and document mining
6 credits
UE Algebra
9 creditsUE Holomorphic functions
6 creditsUE Probabilities
9 creditsUE Analysis
9 credits
UE Study and research work
6 creditsChoice: 3 among 6
UE Effective algebra and cryptographie
6 creditsUE Compléments sur les EDP
6 creditsUE Differential geometry
6 creditsUE Markov process
6 creditsUE Galois theory
6 creditsUE Operations Research (AM)
6 credits
Choice: 1 among 2
UE English S8
3 creditsUE Opening UE (only if C1 level in English reached)
3 credits
UE Advanced models and methods in operations research
6 creditsUE Combinatorial optimization and graph theory
6 creditsUE Optimization under uncertainty
6 creditsUE Constraint Programming, applications in scheduling
3 creditsUE Graphs and discrete structures
3 creditsUE Advanced heuristic and approximation algorithms
3 creditsUE Advanced mathematical programming methods
3 creditsUE Academic and industrial challenges
3 creditsUE Transport Logistics and Operations Research
6 creditsUE Advanced parallel system
6 creditsUE Multi-agent systems
3 creditsUE Fundamentals of Data Processing and Distributed Knowledge
6 creditsUE Scientific Methodology, Regulatory and ethical data usage
6 creditsUE Large scale Data Management and Distributed Systems
6 creditsUE Cryptographic engineering, protocols and security models, data privacy, coding and applications
6 creditsUE From Basic Machine Learning models to Advanced Kernel Learning
6 creditsUE Mathematical Foundations of Machine Learning
3 creditsUE Learning, Probabilities and Causality
6 creditsUE Statistical learning: from parametric to nonparametric models
6 creditsUE Mathematical optimization
6 creditsUE Safety Critical Systems: from design to verification
6 creditsUE Natural Language Processing & Information Retrieval
6 creditsUE Information Security
6 creditsUE Human Computer Interaction
6 creditsUE Next Generation Software Development
6 credits
UE Practicum
30 credits
UE Advanced models and methods in operations research
6 creditsUE Combinatorial optimization and graph theory
6 creditsUE Optimization under uncertainty
6 creditsUE GS_MSTIC_Research ethics
6 creditsUE Constraint Programming, applications in scheduling
3 creditsUE Graphs and discrete structures
3 creditsUE Advanced heuristic and approximation algorithms
3 creditsUE Advanced mathematical programming methods
3 creditsUE Academic and industrial challenges
3 creditsUE Transport Logistics and Operations Research
6 credits
UE Practicum
30 credits
Cybersecurity
The global economic impact of losses due to cybercrime amounts to hundreds of billions of euros per year ($445 billion according to the McAfee/CSIS study of 2014) with a strong increase in attacks, especially for identity theft and digital data theft, as well as malicious attacks.
Protection against these vulnerabilities includes :
- Robustness to cyber attacks of sensitive infrastructure (e.g. stuxnet)
- Robustness of security components against software vulnerabilities and data leaks (e.g. heartbleed)
- Protection of privacy and security of cloud infrastructure
- Robust design and evaluation of safety components
- Fault detection in protocols or software and hardware components
The topics covered in the training cover the complementary areas of Cybersecurity, including cryptology, forensics, and privacy, in particular for embedded systems and distributed architecture.
The objective of this program is to train cybersecurity experts (including data privacy aspects) with a bac + 5 degree, able to evolve immediately in an industrial environment and who can also pursue a thesis.
The course is labelled "Core AI" by MIAI.
UE Object-oriented and software design
3 creditsUE Partial differential equations and numerical methods
6 creditsUE Signal and image processing
6 creditsUE Geometric modelling
6 creditsUE English
3 creditsUE Applied probability and statistics
6 creditsUE Systèmes dynamiques
3 creditsUE Instability and Turbulences
3 creditsUE Turbulence
3 credits
UE Computing science for big data and HPC
6 creditsHPC
Introduction to database
3 credits
UE Project
3 creditsUE Internship
3 creditsUE Numerical optimisation
6 creditsChoice: 2 among 6
UE Operations Research (AM)
6 creditsUE Introduction to cryptology (AM)
6 creditsUE 3D Graphics (AM)
6 creditsUE Turbulences
6 creditsUE Statistical analysis and document mining
6 creditsUE Variational methods applied to modelling
6 credits
UE Object-oriented and software design
3 creditsUE Partial differential equations and numerical methods
6 creditsUE Signal and image processing
6 creditsUE Geometric modelling
6 creditsUE Applied probability and statistics
6 creditsUE English
3 credits
UE Computing science for big data and HPC
6 creditsHPC
Introduction to database
3 credits
UE Project
3 creditsUE Internship
3 creditsUE Numerical optimisation
6 creditsUE GS_MSTIC_Scientific approach
6 creditsChoice: 1 among 6
UE Operations Research (AM)
6 creditsUE Introduction to cryptology (AM)
6 creditsUE 3D Graphics (AM)
6 creditsUE Turbulences
6 creditsUE Variational methods applied to modelling
6 creditsUE Statistical analysis and document mining
6 credits
UE Algebra
9 creditsUE Holomorphic functions
6 creditsUE Probabilities
9 creditsUE Analysis
9 credits
UE Study and research work
6 creditsChoice: 3 among 6
UE Effective algebra and cryptographie
6 creditsUE Compléments sur les EDP
6 creditsUE Differential geometry
6 creditsUE Markov process
6 creditsUE Galois theory
6 creditsUE Operations Research (AM)
6 credits
Choice: 1 among 2
UE English S8
3 creditsUE Opening UE (only if C1 level in English reached)
3 credits
UE Software security, secure programming and computer forensics
3 creditsUE Security architecture
6 creditsUE Cryptographic engineering, protocols and security models, data privacy, coding and applications
6 creditsUE Threat and risk analysis, IT security audit and norms
3 creditsUE Physical Security : Embedded, Smart Card, Quantum & Biometrics
6 creditsChoice: 1 to 2 among 2
UE Advanced cryptology
6 creditsUE Advanced security
6 credits
UE Software security, secure programming and computer forensics
3 creditsUE Cryptographic engineering, protocols and security models, data privacy, coding and applications
6 creditsUE Threat and risk analysis, IT security audit and norms
3 creditsUE Physical Security : Embedded, Smart Card, Quantum & Biometrics
6 creditsUE GS_MSTIC_Research ethics
6 creditsChoice: 1 among 2
UE Advanced cryptology
6 creditsUE Advanced security
6 credits
Statistics and data sciences (SSD)
To view the presentation of the Statistics and data sciences (SSD) program in French click on the following link : Parcours Statistiques et sciences de sonnées (SSD)
Science in industrial and applied mathematics (MSIAM)
Currently, applied mathematics is an area that provides many job opportunities, in industry and in the academic world. There is a great demand for mathematical engineers on topics such as scientific computation, big data analysis, imaging and computer graphics, with applications in many fields such as physics, medicine, biology, engineering, finance, environmental sciences.
The master of Science in industrial and applied mathematics (MSIAM) offers a large spectrum of courses, covering areas where the research in applied math in Grenoble is at the best level. The graduates are trained to become experts and leaders in scientific and technological projects where mathematical modeling and computing issues are central, in industry or research. A large and distinguished graduate Faculty participate in the program, bringing their expertise in a wide range of areas of mathematics including applied analysis, numerical analysis and scientific computing, probability theory and statistics, computational graphics, image analysis and processing, and applied geometry.
The academic program is a two-year master program (120 ECTS), fully taught in English. It combines three semesters of courses and laboratory work (90 ECTS) with a six-month individual research project (30 ECTS). The first year is composed of a common core which provides theoretical and practical grounds in probability and statistics, PDE and modelling, images and geometry as well as computer sciences, optimisation and cryptology.
In the second year, the third semester is divided in 2 tracks :
- Modeling, Scientific Computing and Image analysis (MSCI)
- Data Science (DS)
The semester 10 is devoted to the master thesis project.
The course is labelled "Core AI" by MIAI.
UE Object-oriented and software design
3 creditsUE Partial differential equations and numerical methods
6 creditsUE Signal and image processing
6 creditsUE Geometric modelling
6 creditsUE English
3 creditsUE Applied probability and statistics
6 creditsUE Systèmes dynamiques
3 creditsUE Instability and Turbulences
3 creditsUE Turbulence
3 credits
UE Computing science for big data and HPC
6 creditsHPC
Introduction to database
3 credits
UE Project
3 creditsUE Internship
3 creditsUE Numerical optimisation
6 creditsChoice: 2 among 6
UE Operations Research (AM)
6 creditsUE Introduction to cryptology (AM)
6 creditsUE 3D Graphics (AM)
6 creditsUE Turbulences
6 creditsUE Statistical analysis and document mining
6 creditsUE Variational methods applied to modelling
6 credits
UE Object-oriented and software design
3 creditsUE Partial differential equations and numerical methods
6 creditsUE Signal and image processing
6 creditsUE Geometric modelling
6 creditsUE Applied probability and statistics
6 creditsUE English
3 credits
UE Computing science for big data and HPC
6 creditsHPC
Introduction to database
3 credits
UE Project
3 creditsUE Internship
3 creditsUE Numerical optimisation
6 creditsUE GS_MSTIC_Scientific approach
6 creditsChoice: 1 among 6
UE Operations Research (AM)
6 creditsUE Introduction to cryptology (AM)
6 creditsUE 3D Graphics (AM)
6 creditsUE Turbulences
6 creditsUE Variational methods applied to modelling
6 creditsUE Statistical analysis and document mining
6 credits
UE Differential Calculus, Wavelets and Applications
6 creditsUE An Introduction to Shape and Topology Optimization
3 creditsUE Efficient methods in optimization
3 creditsUE Computational biology
3 creditsUE Fluid Mechanics and Granular Materials
6 creditsUE GPU Computing
6 creditsUE Software development tools and methods
3 creditsUE Geophysical imaging
3 creditsUE Handling uncertainties in (large-scale) numerical models
6 creditsUE Modeling seminar and projects
6 creditsUE Quantum Information & Dynamics
6 creditsUE Optimal transport: theory, applications and related numerical methods
6 creditsUE Statistical learning: from parametric to nonparametric models
6 creditsUE Temporal, spatial and extreme event analysis
6 credits
UE Research projects
30 credits
UE Advanced Machine Learning: Applications to Vision, Audio and Text
6 creditsUE An Introduction to Shape and Topology Optimization
3 creditsUE Computational biology
3 creditsUE Data Science Seminars and Challenge
6 creditsUE Differential Calculus, Wavelets and Applications
6 creditsUE Efficient methods in optimization
3 creditsUE From Basic Machine Learning models to Advanced Kernel Learning
6 creditsUE Handling uncertainties in (large-scale) numerical models
6 creditsUE GPU Computing
6 creditsUE Learning, Probabilities and Causality
6 creditsUE Mathematical Foundations of Machine Learning
3 creditsUE Modeling seminar and projects
6 creditsUE Optimal transport: theory, applications and related numerical methods
6 creditsUE Natural Language Processing & Information Retrieval
6 creditsUE Statistical learning: from parametric to nonparametric models
6 creditsUE Software development tools and methods
3 creditsUE Temporal, spatial and extreme event analysis
6 credits
UE Research projects
30 credits
UE GS_MSTIC_Research ethics
6 creditsUE Software development tools and methods
3 creditsUE Modeling seminar and projects
6 creditsUE Geophysical imaging
3 creditsUE An Introduction to Shape and Topology Optimization
3 creditsUE Refresh courses
0 creditsUE GPU Computing
6 creditsUE Differential Calculus, Wavelets and Applications
6 creditsUE Optimal transport: theory, applications and related numerical methods
6 creditsUE Fluid Mechanics and Granular Materials
6 creditsUE Handling uncertainties in (large-scale) numerical models
6 creditsUE Temporal, spatial and extreme event analysis
6 creditsUE Advanced Machine Learning: Applications to Vision, Audio and Text
6 creditsUE Natural Language Processing & Information Retrieval
6 creditsUE From Basic Machine Learning models to Advanced Kernel Learning
6 creditsUE Mathematical Foundations of Machine Learning
3 creditsUE Statistical learning: from parametric to nonparametric models
6 creditsUE Learning, Probabilities and Causality
6 creditsUE Efficient methods in optimization
3 creditsUE Data Science Seminars and Challenge
6 creditsUE Computational biology
3 creditsUE Quantum Information & Dynamics
6 creditsUE Numerical Mechanics
6 credits
UE Research projects
30 credits