Mathematics, Modeling, and Machine Learning track

Keywords: Machine Learning, Big data, Biostatistics, Optimization, Image processing, Computer vision.

 

The Master in Mathematics, Modeling, and Machine Learning features a common-core curriculum in the first year and a second year that offers students several options.

The first year focuses on several aspects of applied mathematics. The purpose of this year is to provide students with a solid basic education in analysis, probability, and statistics while preparing them for the tracks offered during year two.

The second year of the master’s program offers advanced training in probability, statistics, mathematical modeling, image processing, and mathematical applications related to the life sciences topics studied at the MAP5 Laboratory.

Students who complete the first year of the Master in Mathematics, Modeling, and Machine Learning can also apply to the Master in Mathematics, Computer Vision, and Machine Learning through an educational partnership with Paris Saclay University and Paris Descartes University.

 
Requirements

The Mathematics, Modeling, and Machine Learning specialty is open to students with a Bachelor in Mathematics (or an equivalent French or international degree). Students who would like to apply directly to the second year of the master’s program must have already completed the first year of a Master in Mathematics and have a thorough understanding of probability and statistics.

 
Goals

Training specialists in random and deterministic modeling and machine learning in preparation for careers in imaging or life sciences (biology, health, medicine).

The goal is to train specialists in applied mathematics. The program is designed for students who would like to specialize in probability, statistics, image processing, or digital and deterministic modeling. Career opportunities include research-oriented professions (doctoral thesis) in the public sector as well as R&D departments in private companies, as well as any profession that involves image analysis or data.

The first year of the master’s program offers a solid education in mathematics and applied mathematics.
The second year of the program teaches optimization and machine learning techniques, with a special focus on probabilistic modeling, biostatistics, and image processing.

 

Lecturers: The lecturers featured in the program are research professors from the Information Technology and Mathematics TRU, the Biomedical TRU, members of the MAP5 Laboratory (CNRS Mixed Research Unit 8145), and researchers from INRA, CNRS, and the Institute of Radio-Protection and Nuclear Safety (IRSN).

 

 
Career and continuing education opportunities
  • Public research (university, CNRS, INRIA, CEA, CNES, INRA, INSERM, etc.) and hospital research departments
  • Industry (Alcatel, Sagem, General Electric, Thales, etc.)
  • Pharmaceutical companies (GSK, Sanofis-Aventis)
  • Thesis in university laboratories or with private company research teams
  • Engineers specialized in imaging or biostatistics
 
Application process

Click here.

 

Directors

1st year : Sylvain DURAND

2d year : Julie DELON

Possibilities during the second year of the master’s program:

Students who complete the first year of the program can also apply to the second year of the Master in Mathematics, Computer Vision, and Machine Learning through an educational partnership with Paris Saclay University and Paris Descartes University.

2d year : Mathematics, Computer Vision, and Machine Learning

The Mathematics, Computer Vision, and Machine Learning track is co-accredited through ENS Cachan, École Polytechnique, TELECOM ParisTech, École Centrale de Paris, École Nationale des Ponts et Chaussées, and Université Paris Dauphine.

Goals

The Mathematics, Computer Vision, and Machine Learning track offers advanced mathematical and experimental training in analysis and probability that allows students to study a full range of high-level IT and mathematical concepts, models, and techniques that are applicable to computer vision, perception, and machine learning by focusing on active research topics, including artificial vision, automatic signal and image analysis, and the emulation of perceptive and adaptive human behavior. The master’s program is geared towards the rapid and fascinating development of the application of mathematics to modeling and the emulation of human intelligence. This development is in turn supported by the rapid rise of brain sciences.

Career and continuing education opportunities

In terms of professional opportunities, students who have successfully defended a thesis or earned a PhD through this type of master’s program can apply to positions at major French-European research laboratories, both private (Aerospace, Alcatel, Sagem, General Electric, Matra, Philips, Siemens, Thomson, Xerox, etc.) and public (CEA, CNES, INRA, INRIA, ISPRA, LETI, etc.).

Students can continue their education through applied mathematics departments or certain information technology departments.

 

Directors

Julie DELON

Stéphanie ALLASSONNIERE

 

Ecole Normale Supérieure Paris-Saclay website.