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Master Year 2 Mathematics, Vision, Learning

Master Year 2 Mathematics, Vision, Learning
Year

Master Year 2

Program

Mathematics, Vision, Learning

ECTS Credits

60

Language

English and French

Orientation

Industry and Research

Location

mostly ENS Paris Saclay, also Palaiseau Campus, ENS Ulm, Centrale 

Course duration

12 months, full time

Course start

September

Degree awarded

Master’s degree

WHY ENROLL IN THIS PROGRAM?

Asset n° 1 

Follow a wide range of mathematics courses rooted in applied fields

Asset n°2

Become an expert in the highly sought-after fields of numerical data acquisition, processing and automatic interpretation

Asset n°3

Pursue a career in research or SMEs and innovative startups in the digital world

As more and more numerical data is used in science, technology and society, there is a growing need for top-level researchers in mathematics with expertise in numerical data acquisition, processing and  automatic interpretation. The Mathematics, Vision and Learning Year 2 Master brings together these skills and knowledge with the aim of training tomorrow’s experts.  

The courses offered are driven by data and problems from the real world focusing on scientific fields and industrial and medical applications. Many mathematical topics are also covered including signal representation techniques, variational methods and partial differential equations in image analysis, compressed sensing, probability learning theory, random matrices, convex optimization, theory of shape space, kernel learning methods, graphic models, Markovian simulation learning, control theory and reinforcement learning.

Objectives

This program enables students to:

  • Discover a wide range of concepts, models and algorithms
  • Undertake research topics at the numerical interface of mathematics
  • Learn about all aspects of an applied research project including validating methodologies and algorithms via numerical experiments on real data
  • The main openings for MVL graduates are in applied research with large research bodies (CNRS, CEA, CNES, INRIA, INRA, INSERM, etc.) or the R&D centers of big companies like SAFRAN, General Electric, Technicolor, Saint-Gobain, SAGEM, Dassault Systèmes, Xerox
  • Most students engage in a PhD program either in an industrial or academic laboratory
  • In recent years, SMEs and innovative startups in the digital world, in France and abroad, are increasingly looking for this kind of profile

Admission requirements

Academic prerequisites

  • Completion of the first year of Master in mathematics at Institut Polytechnique de Paris or equivalent in France or abroad
  • Motivated computer scientists with a very good level in mathematics will also be considered

Language prerequisites

  • English
  • French

How to apply

Applications can be submitted exclusively online. You will need to provide the following documents:

  • Transcript
  • Two academic references (added online directly by your referees)
  • CV/resume
  • Statement of purpose

You will receive an answer in your candidate space within 2 months of the closing date for the application session.

Fees and scholarships

Registration fees are available here

Find out more about scholarships

Please note that fees and scholarships may change for the following year.

Applications and admission dates

Coordinators

Yann Gousseau

Program office

Danielle Deloy

General enquiries

master-admission@ip-paris.fr

Description

As more and more numerical data is used in science, technology and society, there is a growing need for top-level researchers in mathematics with expertise in numerical data acquisition, processing and  automatic interpretation. The Mathematics, Vision and Learning Year 2 Master brings together these skills and knowledge with the aim of training tomorrow’s experts.  

The courses offered are driven by data and problems from the real world focusing on scientific fields and industrial and medical applications. Many mathematical topics are also covered including signal representation techniques, variational methods and partial differential equations in image analysis, compressed sensing, probability learning theory, random matrices, convex optimization, theory of shape space, kernel learning methods, graphic models, Markovian simulation learning, control theory and reinforcement learning.

Objectives

This program enables students to:

  • Discover a wide range of concepts, models and algorithms
  • Undertake research topics at the numerical interface of mathematics
  • Learn about all aspects of an applied research project including validating methodologies and algorithms via numerical experiments on real data
  • The main openings for MVL graduates are in applied research with large research bodies (CNRS, CEA, CNES, INRIA, INRA, INSERM, etc.) or the R&D centers of big companies like SAFRAN, General Electric, Technicolor, Saint-Gobain, SAGEM, Dassault Systèmes, Xerox
  • Most students engage in a PhD program either in an industrial or academic laboratory
  • In recent years, SMEs and innovative startups in the digital world, in France and abroad, are increasingly looking for this kind of profile

Admission requirements

Academic prerequisites

  • Completion of the first year of Master in mathematics at Institut Polytechnique de Paris or equivalent in France or abroad
  • Motivated computer scientists with a very good level in mathematics will also be considered

Language prerequisites

  • English
  • French

How to apply

Applications can be submitted exclusively online. You will need to provide the following documents:

  • Transcript
  • Two academic references (added online directly by your referees)
  • CV/resume
  • Statement of purpose

You will receive an answer in your candidate space within 2 months of the closing date for the application session.

Fees and scholarships

Registration fees are available here

Find out more about scholarships

Please note that fees and scholarships may change for the following year.

Applications and admission dates

Coordinators

Yann Gousseau

Program office

Danielle Deloy

General enquiries

master-admission@ip-paris.fr