Objectives and Openings
The "Mathematics of Randomness" degree program provides top-level training in probability, statistics and machine learning.
One of its objectives is to teach students to model and study random phenomena so that they will be able to develop applications for randomness in other scientific disciplines: in particular, probability in physics (theoretical and statistical physics) or biology and statistics in information theory, signal theory, environment or biology.
The other objective is to provide training in statistical learning and data science methods and tools. The wide range of courses offered enables theoretical, applied, algorithmic, and IT aspects of these fields to be explored.
There are two final specializations: "Probability & Statistics" and "Statistics & Machine Learning". The former focuses especially on mathematical research, while the latter leans more towards research or openings in companies.
At the start of the year, each student meets individually the professors in charge of the master program, in order to discuss its personal project. A program of courses is chosen by students and validated by the teaching team. In the "Statistics and Machine Learning" final specialization, the data mining project and the seminar are mandatory.
Anticipated openings are a PhD in mathematics, applied mathematics, or at the interface of mathematics, in an academic or company laboratory. Graduates will also be able to start work in the following sectors: insurance, banking, pharmaceutical laboratories, big companies (climate, energy, and transport), industries (aeronautics, communication, signaling, etc.).
Who to contact?
- Coordinator "Probability & Statistics": Nicolas Curien
- Coordinator "Statistics & Machine Learning": Matthieu Lerasle
- Secretariat: Séverine Simon (Proba & Stat) and Nicolas Apoteker (SML)