Catalogue des formations supérieures aérospatiales
Master of Science in Industrial and Applied Mathematics (MSIAM)
- Organisme: Grenoble INP - Ensimag
- Type de formation : Formation initiale - Formation continue
- Langue(s) utilisée(s) pour la formation : Français, Anglais
- Lieu : Grenoble (Région : Auvergne-Rhône-Alpes)
- Diplôme préparé/grade/titre : MSc : Master of Sciences (Label de la Conférence des Grandes Ecoles)
- Niveau d'entrée : Bac + 3
Détails de la formation
Objectifs : 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.
It is a highly competitive, two-year European Standard (LMD) graduate program, taught in English, offering training on:
Data Science
Modeling, Scientific Computing and Image Analysis.
Specificities
Our 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.
Niveau de Diplôme (UE) : 7 - (Niveau CEC ou équivalent)
Site web dédié : https://ensimag.grenoble-inp.fr/fr/formation/master-of-science-in-industrial-and-applied-mathematics#page-presentation
Domaines
- Sciences et Techniques de l'Ingénierie
Thèmes
- 11 - Informatique, Mathématiques Appliquées, Modélisation, Optimisation, Sciences du numérique et des données, Cryptographie, Cybersécurité, Intelligence Artificielle