Target level
Baccalaureate +5
ECTS
120 credits
Duration
2 years
Component
Grenoble INP - Phelma (Physique, électronique et matériaux), UGA, Grenoble INP - Ense3 (Energie, eau, environnement), UGA
Language(s) of instruction
French, English
Presentation
Course co-accredited by the National Polytechnic Institute of Grenoble (Grenoble INP) and Université Grenoble Alpes
This master takes into account developments in techniques and knowledge in the field of signal and image processing. In particular, it offers an approach with a greater focus on tools for modelling, analysing and formatting information, enabling the transition to the massive data scale.
The course will benefit from the resources of the CEA-GIPSA "common laboratory" (CEA/Grenoble-INP framework agreement), which has been active since 2008. This project has already resulted in the creation of more than eight areas of cooperation, which have led to more than 10 doctorates being supported.
The master's strong foundation within the Université Grenoble Alpes and the SICOM engineering course of the Grenoble INP-ENSE3 and PHELMA components enables the shared organisation of exchanges, lectures and seminars offered by the industrial partners of the engineering courses (Thalès, Trixel, STMicro, EDF, Areva, ...).
Two representatives from the world of R&D (if possible from companies with a broad international base) will be invited to participate in the training development committee.
- Doctorate in the field of ICST
- Employment in R&D in the industrial sector, in SIP or information science
International education
Internationally-oriented programmes
International dimension
The course has an international orientation, with 100% of the teaching for 2nd year's master provided in English. For foreign students enrolled in the 1st year, courses in French as a foreign language may be offered. The training offer will be circulated to foreign universities that are already partners of ENSE3 and PHELMA in the framework of their engineering courses.
Organisation
Program
Specifics of the program
- Master 1st year : The very close cooperation between the first and the second year of the SICOM course means that it is not possible to guarantee that 100% of the teaching will be in English. All supporting documents will however be available in English.
- Master 2nd year : 12 ECTS shared with the third year of SICOM; these comprise the "basic" courses in the field. 3 ECTS can be replaced by courses selected from the Université Grenoble Alpes training offer, to be determined at the beginning of the year with the course managers. These must be courses in a scientific field related to the themes of the master. More than just an introduction, these courses should help reinforce knowledge on more specific methodological aspects, related to SIP. 18 original ECTS, broken down into two fundamental modules (6 ECTS each) and one research introduction module (6 ECTS), established on the basis of a winter school and a cycle of seminars. These modules that are not shared with SICOM (12 ECTS) are established on the basis of three courses. If agreed by their master managers, the students will be able to replace one course in each module by an opening course from the other masters of the site (Sciences Co, MisCit, MSIAM, Astro, Geoscience). All of the teaching and supporting documentation (100%) for the 2nd year's master is in English. The end-of-course internship (27 ECTS) and the language courses (3 ECTS) round off the training.
Select a program
Signal image processing methods and applications
The SIGMA master provides students the tools to deepen their knowledge and develop their expertise in the field of digital signal and image processing, computer sciences and information technologies. A particular emphasis is put on fundamental skills and tools for signal and systems modeling, information extraction from experimental data as well as information representation and conditioning.
The program is dedicated to provide the students the necessary competences to become creative specialists in various areas involving numerical technologies, such as biomedical signal processing, observational sciences (geosciences, monitoring, remote sensing,), artificial intelligence (machine learning, statistical inference, computational Bayes methods) to mention a few. The master is designed to prepare for PhD studies in the fields of electrical engineering and computer sciences, with a focus on digital methods. An important part of the lectures is dedicated to introduce present research and development topics ; this teaching is organized into a series of short lectures given by professional and researchers from companies or labs developing research or applications in the field of information technologies.
A 5 to 6 months internship in a research lab or in a company involved in R&D is part of the cursus.
Mobile, autonomous and robotic systems
Mobile, autonomous and robotic systems (MARS) is an advanced academic program on mobile robotic and autonomous systems. This highly competitive program includes advanced courses in artificial intelligence, control theory, drones, embedded systems, diagnostic and reliability, cybersecurity and intelligent mobility. In addition, a 5 to 6-month internship, is conducted in a laboratory or within an industrial research center.
The Master degree in Robotics and Autonomous Systems aims at offering an international master program that allows a better understanding of technical and scientific aspects of connected and autonomous mobile robotic systems and to understand their interactions.
It englobes an advanced academic program on:
- Mobile and aerial robots that can act and evolve autonomously in complex environments.
- Perception for detection and tracking of moving objects.
- Navigation and Path Planning
- Robotic operating system (ROS)
- Artificial intelligence planning for autonomous robots requiring little or no supervision
- Machine learning
- Advanced methods for optimal control and predictive control
- Methods to monitor and diagnose dynamic systems with a study on the reliability of a systems subject to failure
- Distributed optimization and game theory
- Embedded systems: microcontrollers architectures and sensors for robotics
- Cyber-security: Make risk analysis, detect cyber-attacks and develop strategies. Implement some cyber-security mechanisms, on the communication infrastructure and on the robot systems
- Intelligent mobility and transportation to improve the safety of the vehicle and the comfort of the passengers, as well as the detection and reconfiguration of the controllers in case of emergency.
- Multi-vehicle coordination, in the perspective of understanding the behavior of groups of autonomous and non-autonomous robotic systems.
Admission
Access conditions
To be accepted for a master 1st year, you must hold a bachelor degree (licence 3rd year) or equivalent.
To be accepted for a master 2nd year, you must hold a master 1st degree or equivalent. Your previous studies must be compatible with the master you wish to study. The recruitment and registration conditions are stated for each speciality
Candidature / Application
Students
15 students in 1st year and 15 to 20 students in 2nd year
And after
Further studies
Doctorate in the field of ICST
Sector(s)
- Modelling of signals and systems, random processes
- Formatting, extraction and analysis of information in complex observation systems : inverse problems, detection, statistical learning. Transition to the scale of large masses of data
- Applications in multi- and hyperspectral imaging, biomedical applications, neurosciences, astro, geosciences etc
Additional information
- The master falls within the Data Sciences theme of the Université de Grenoble Alpes community's MSTIC cluster
- Involvement of local excellence laboratories: Persyval, Osug@2020
- Involvement in regional initiatives: IXXI, SIERA
- Main support laboratories: GIPSA-Lab (Grenoble), IPAG (Grenoble), LISTIC (Annecy), ENS-Lyon Physics Lab
- Partner laboratories: LJK, LIG, G2ELab, LTHE, LEGI