Over one year, you will receive on-site training in mathematics, encompassing both pure mathematics and applied mathematics as well as take courses from UniCA's Mod4NeuroCog. MFA's main objective is to prepare you to integrate into the world of theoretical or applied mathematical research.

Through MFA, you will cultivate skills in various areas of mathematics to tackle complex phenomena found in fields such as finance, biology, and physics and specialize in one of three specific mathematical fields: Algebra and Geometry, Analysis-Scientific Computation or Probability-Statistics. Through this specialization, you will develop a solid understanding of your chosen area and gain  in-depth knowledge and expertise. 
 


MPA Class
MPA Class


By focusing on a specific mathematical field, you will be able to explore advanced topics and applications related to your research interests. With approval of your coordinator, you may also create a customized program comprising one specialization along with courses in for instance, PDEs/or stochastic processes. During your studies, you will have the option to do a 3-month research internship or pursue a thesis.
 
 

Thematic Blocks

 
Algebra Geometry
Algebra Geometry


Algebra-Geometry

Analysis
Analysis


Analysis

Probability & Stats
Probability & Stats


Probability and Statistics

 
 

Program Information

     
Dates
  
2027-28 Application Period May 2027 - July 2027
2026-27 Course Dates September 11th, 2026 - mid July 2027
Internship Period March - June (TBC)
Semester 1


 

Algebra Block

Subject Value
Riemann Surfaces / Algebraic Geometry

6 ECTS
Analysis and Tools for PDE 6 ECTS
Advanced Geometry 6 ECTS

Analysis Block

Subject Value
Numerical Methods for Partial Differential Equations 6 ECTS
Functional Analysis 6 ECTS
Analysis and  Tools for PDE 6 ECTS

 

Semester 2
 

Algebra Block

Subject Value
Analysis on Manifolds

6 ECTS
Dynamical Systems 6 ECTS

Analysis Block

Subject Value
Advanced methods for numerical Analysis 6 ECTS
Advanced PDE 6 ECTS
 
 
Course Schedule 2026/2027


Unless otherwise specified, all courses are in salle 1 in Dieudonné 1 and that will remain your regular classroom until the end of the year for the Algebra and the Analysis blocks.
Thursdays mornings are kept free for EUR Spectrum minors.

First Trimester


Welcome meeting: Friday  September 11th, 2026 at 2pm in salle 1.

The first trimester starts September 14th through November 2026, with exams in the week from November 30 to December 4.

The 2nd trimester starts the week of December 7, 2026 through February 2027, with exams to be scheduled on the week of March 1, 2027.

Masters thesis: The students will have found their subject and director by  January 2027. Starting with March 2027 the students will work on their mémoire (=masters thesis), and the first defences are mid-June 2027, and can be until September 2027, depending on the future plans of the students.

Algebra Block

Mondays  14:00-16:00 Riemann surfaces/Algebraic Geometry SMUFA 301 Michele Ancona

Tuesdays 14:00-16:00 :  Analysis and  Tools for PDE SMUFA 304 Rémy Rodiac

Wednesdays 14:00-16:00:  Analysis and  Tools for PDE SMUFA 304 Rémy Rodiac

Wednesdays 8:30-12:30 : Advanced Geometry SMUFA 310 Khazhgali Khozhasov

Fridays 10:30-12:30 : Riemann surfaces/Algebraic Geometry SMUFA 301 Michele Ancona

Analysis Block

Mondays 10:30-12:30: Numerical Methods for Partial Differential Equations SMUFA 305-Sebastian Minjeaud

Tuesdays 8:30-12:30: Functional Analysis SMUFA 303-Isabelle Tristani

Tuesdays 14:00-16:00 : Analysis and  Tools for PDE SMUFA 304 -Rémy Rodiac

Wednesdays 14:00-16:00: Analysis and Tools for PDE SMUFA 304 – Rémy Rodiac

Fridays 14:00-16:00: Numerical Methods for Partial Differential Equations SMUFA 305-Sebastian Minjeaud

Second trimester

Algebra Block

Mondays  10:15-12:15: Analysis on Manifolds  SMUFA 309 Ursula Ludwig

Tuesdays 8:00-10:00: Analysis on Manifolds  SMUFA 309 Ursula Ludwig

Wednesdays 14:00-16:00 Dynamical Systems SMUFA 300 : Emmanuel Militon

Fridays 14:00-16:00: Dynamical Systems  SMUFA 300 : Emmanuel Militon

Analysis Block

Mondays 13:00-16:00: Advanced methods for numerical Analysis SMUFA 312-Stella Krell

Tuesdays 10:00-13:00: Advanced methods for numerical Analysis SMUFA 312-Stella Krell

Wednesdays 10:00-12:00: Advanced PDE SMUFA 311-Thierry Goudon

Fridays 10:30-12:30: Advanced PDE SMUFA 311-Thierry Goudon

Probability and Statistics Block

First trimester:


Common to All Students

Stochastic Calculus and Applications, Rémi Catellier, Room 2 (Dieudonné)

            Tuesday 08:30-12:30 (Sep. 14 —Dec. 8)

            Tuesday Sep. 15, Sep. 22, Sep. 29, 13:00-16:00

            see Google agenda

Probabilistic Computational Methods,  Etienne Tanré, Room 2 (Dieudonné)

            Tuesday 13:00-16:00 (Oct. 6 — Dec. 15)

            see Google agenda


Additional for PS and Mathmods Students

Introduction to generative AI, Marco Corneli, Stéphane Descombes & Samuel Vaiter

            Wednesday 09:00-12:00 (Sep. 14—Nov. 25)

                see Google agenda

Geometric Statistics, Khazghali Kozhasov

            Monday 08:30-12:30 (Sep. 15—Nov. 16)

            except Monday Oct. 12 —> Friday Oct. 16 14:00—18:00


Additional for InterMaths

Introduction to Neuroscience

            Wednesday Sept 16 14:00—17:00, Raphael Fargier, Room 383 Lucioles

            Wednesday Sept 23 14:00—17:00, Raphael Fargier, Room 383 Lucioles

            Thursday Sept 24 10:00—13:00, Ingrid Bethus, Room 383 Lucioles

            Thursday Oct 1st 10:00—13:00, Ingrid Bethus, Room 383 Lucioles

DeepL (as part of Artificial Networks), Pierre-Alexandre Mattei and Rémi Sun, Room 383 Lucioles

            Wesdneday afternoon, to be confirmed, starting from October

Models in Neurocognition, Patricia Reynaud &Etienne Tanré, Room 383 Lucioles                                  

            Monday morning, to be confirmed, starting  from November

Behavioral and Cognitive Neuroscience, Paule Pousinha, Room 383 Lucioles

            Monday/wednesday afternoon, to be confirmed, starting  from November

Second trimester


Common to All Students

Advanced stochastic (including stochastic for large networks), François Delarue, Dieudonné

Additional for PS and Mathmods Students

Statistical learning from and on Graphs, Marco Corneli, Dieudonné

Fundamentals in Machine Learning, Yassine Laguel, Dieudonné