Overview
Master
National diploma- Degree awarded Master
- Mention
- Signal and Image Processing
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Location
- GRENOBLE Scientific Polygon
- Duration 1-year program
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Available as
- Initial education
Objectives
The IMAGERS Master’s program focuses on data science (signal and image processing) and artificial intelligence (particularly deep learning methods) as applied to remote sensing in the fields of geosciences, Earth observation, and environmental monitoring.
Its goal is to train experts capable of designing, developing, and deploying intelligent digital systems to analyze data obtained through various imaging modalities (optical, radar, hyperspectral, lidar, thermal) in a variety of contexts. The program includes advanced courses in signal processing, image processing, artificial intelligence, and data science—cross-disciplinary skills central to the digital field.
It trains professionals capable of designing and operating complex digital systems in conjunction with industrial and/or natural systems.
Specificities
The program lies at the intersection of AI, computer vision, data science, remote sensing, and geosciences.
Earth observation, for example, will enable the development of applications for natural resource management and the monitoring of forest ecosystems. These skills can be directly applied by professionals in agriculture, the agri-food industry, and forestry—sectors that are strategic for the environmental transition.
Accreditation:
The IMAGERS International Master’s program is accredited by EFELIA - MIAI (Multidisciplinary Institute in Artificial Intelligence), a leading center in the field of artificial intelligence.
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Training partners
Laboratories
INRIA, IGE, IsTerre, GIPSA-Lab
Entreprises
Lynred company, Datlas Ocean, Airbus, Safran, Ariane Group
Admission
- required training M1 Level
Data science and an interest in environmental science, mathematics, applied physics, geophysics, and geosciences, with an interest in computer science
Students must have prior knowledge of machine learning (basic concepts of supervised and unsupervised methods, including ensemble methods and random forests) as well as deep learning (CNN, RNN, LSTM). They must also be proficient in Python programming. - Tuition fees Tuition rates for academic year : 5180 euros
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Available as :
- Initial education
Apply now
Application period : October through May
Decision : on a rolling basis
Contacts
General information
IMAGERS is led by Jocelyn Chanussot, INRIA Research Director and Professor at Grenoble INP-UGA, and Sophie Giffard-Roisin (Researcher, IsTerre Laboratory).
Cornel Ioana (Associate Professor at Grenoble INP-UGA, GIPSA-Lab) is in charge of industry relations.
Mauro Dalla Mura (Associate Professor at Grenoble INP-UGA, GIPSA-Lab) is in charge of international relations.
Academic information
Head of the master
Jocelyn CHANUSSOT
Administrative Contact
International Relations Ense3
Education contact
Program
- Course duration 1-year program
International
- Internship abroad No
International mobility
Partnerships with Foreign Universities
The master’s program offers the opportunity to complete an internship abroad. In particular, the program has strong ties with numerous universities in Italy, Spain, Germany, Sweden, Norway, Iceland, Switzerland, Japan, China, the United States, India, Australia, and more…
Prospects
Careers
The geosciences use remote sensing as a tool to better understand the Earth. These cutting-edge skills are in high demand worldwide in engineering, whether in research and/or industry.
This program paves the way for a variety of careers involving AI and environmental monitoring: Data Science Engineer at environmental consulting firms, in satellite imaging for energy, water, and the environment, and more broadly in the geosciences.
The program’s cross-disciplinary skills in artificial intelligence and computer vision also open up opportunities to work in other sectors (biomedical, multimedia, quality control via machine vision, defense and security, etc.).
International Students and Scholar Offices - ISSO
→ https://international.univ-grenoble-alpes.fr/en/