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. 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.

By the end of the program, students in MSIAM should be able to formulate a well posed problem in mathematical terms, carry out appropriate mathematical analysis, propose an appropriate numerical method, implement a program which provide adequate answers to the question, and present and interpret these results.

The emphasis of the Grenoble community is to create the link between the study of the mathematical problem inferred from the application and the practical resolution, ideally in a framework that allows for reproductible results.

The academic program is a one-year Master program (60 ECTS), fully taught in English. It combines one semester of courses and laboratory work (30 ECTS) with a six-month individual research project (30 ECTS).

  • The fall semester is divided into tracks

    • Modeling, Scientific Computing and Image analysis (MSCI)
    • Data Science (DS)
  • However a personalized track may also be build for some students from the available courses (if no timetable conflicts appears). The personalized tracks must be approved by the Professors in charge of MSIAM.

  • The spring semester is devoted to the master thesis project.

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 (see also the possible job titles for people with backgrounds in applied maths).