The M1 Hadamard program at ENS is an advanced master's degree program that covers a broad spectrum of mathematical skills and introduces students to research via a three-month research project.
The primary target audience is second-year students at ENS Paris-Saclay. The program is designed to help students formalize a doctoral project in any branch of mathematics. The M1 Hadamard program at ENS provides students with the opportunity to gain a solid foundation in mathematics by taking in-depth, cross-disciplinary, and specialized courses at ENS, the Faculty of Sciences in Orsay, or the École Polytechnique. Students also participate in a three-month research project in an academic or non-academic laboratory in France (outside the Île-de-France region) or abroad. It provides an opportunity to learn about the various approaches to conducting research in mathematics.
Information
Skills
- Master advanced mathematical concepts and theories.
- Apply mathematical calculations, tools, and methods.
- Research and summarize the current state of knowledge regarding a mathematical problem.
- Analyze a research document to summarize and exploit it in order to judge its relevance.
- Develop mathematical intuition, formulate conjectures, verify their relevance, and compare them with the current state of knowledge.
- Design and construct rigorous mathematical proofs independently.
- Master standard digital tools and programming languages.
- Communicate research results. Write a mathematical text according to the discipline's conventions. Create an oral presentation that highlights the state of the art, the original research, and the mathematical techniques used.
Objectives
- Acquérir, comprendre et maîtriser un grand nombre d'outils et de méthodes mathématiques d'un haut niveau sans aucun cloisonnement, en proposant un spectre étendu de cours classiques, mais aussi originaux dans l'ensemble des domaines des mathématiques.
- Découvrir l'activité de recherche en mathématiques en se confrontant à des problématiques ouvertes et actuelles à l'occasion des journées de rentrée et d’un projet de recherche de 3 mois.
Career Opportunities
Career prospects
Academic staff
Research & Development Engineer
Research Engineer
Further Study Opportunities
PhD
Calendar
Admission Route
Capacity
Available Places
Target Audience and Entry Requirements
A very good command of the mathematical concepts covered in a bachelor's degree in mathematics
Application Period(s)
From 01/06/2026 to 30/06/2026
Supporting documents
Compulsory supporting documents
Motivation letter.
All transcripts of the years / semesters validated since the high school diploma at the date of application.
Curriculum Vitae.
Additional supporting documents
Letter of recommendation or internship evaluation.
Certificate of French (compulsory for non-French speakers).
Detailed description and hourly volume of courses taken since the beginning of the university program.
VAP file (obligatory for all persons requesting a valuation of the assets to enter the diploma).
Recommendation letters.
Supporting documents :
- Residence permit stating the country of residence of the first country
- Or receipt of request stating the country of first asylum
- Or document from the UNHCR granting refugee status
- Or receipt of refugee status request delivered in France
- Or residence permit stating the refugee status delivered in France
- Or document stating subsidiary protection in France or abroad
- Or document stating temporary protection in France or abroad.
| Subjects | ECTS | Semester | Lecture | directed study | practical class | Lecture/directed study | Lecture/practical class | directed study/practical class | distance-learning course | Project | Supervised studies |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Advanced courses | |||||||||||
| Advanced Algebra | 7.5 | Semester 1 | 48 | 60 | |||||||
| Advanced analysis | 7.5 | Semester 1 | 48 | 60 | |||||||
| Advanced Probability Theory | 7.5 | Semester 1 | 48 | 60 | |||||||
| Transversal skills | |||||||||||
| Signal and information Theory | 5 | Semester 2 | 20 | 20 | |||||||
| Optimization and numerical optimization | 5 | Semester 2 | 20 | 14 | 6 | ||||||
| Mathematical statistics | 5 | Semester 2 | 20 | 14 | 6 | ||||||
| Statistical learning | 5 | Semester 2 | 20 | 14 | 6 | ||||||
| Functional Analysis | 5 | Semestre 1 | 20 | 20 | |||||||
| Differential Geometry and the Calculus of Variations | 5 | Semester 2 | 20 | 14 | 6 | ||||||
| Discretization of PDEs | 5 | Semestre 2 | 20 | 20 | |||||||
Teaching Location(s)
Training campus
Saclay Moulon
Contact
-
Frédéric PASCAL
PR