Mathematics and Applications

Overview

This specialisation provides a broad-based curriculum in applied mathematics, from the core notions in analysis and probability to more applied vocational concepts in statistics or scientific computing.

The multidisciplinary nature of this specialisation represents an advantage across a wide range of sectors requiring a sound understanding of mathematical tools and concepts in order to meet new technical and economic challenges. The aim is not only to provide a solid grounding in mathematics, but also a good grasp of topical issues. The lecturers lead research activities linked to different industrial sectors (aerospace, nuclear power, energy, environment, health, finance etc). This gives the students exposure to the practical applications of mathematical tools and concepts and possible career orientations.

Two tracks are on offer within the specialisation: 'Statistics and Data Science' and 'Numerical analysis and probability'.

Some courses are taught jointly in conjunction with the Master Mathématiques et Applications at the University of Nantes.

Contribution to sustainable development goals

SDG 7 - AFFORDABLE AND CLEAN ENERGY

SDG 9 - INDUSTRY, INNOVATION AND INFRASTRUCTURE

► Learn more about Centrale Nantes' commitment to the 17 sustainable development goals

Admission

International students can follow this specialisation, taught in French, via:

A double degree programme - Open to international students selected by our partner institutions. Selected students spend two years studying courses from the engineering programme at Centrale Nantes. This usually includes one year of the common-core engineering curriculum followed by one year of specialisation. Double degree students are typically accepted after successfully completing two or three years of higher education in their home institution.
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The fast-track engineering programme: Open to students with a Bachelor's or equivalent degree in science. Our fast-track programme gives international students who are qualified to bachelor level the opportunity to gain the 'diplôme d'ingénieur' in just two years.
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Course Content

2024/25 Academic Year

Autumn Semester	Spring Semester
Core Courses:
Functional analysis	Advanced statistical learning
Statistical learning	Uncertainty quantification
Probability	Project 2
Probabilistic numerical methods	Internship
Stochastic processes
Project 1
Numerical analysis and probability Track:
Numerical analysis	Stochastic modelling
Partial differential equations	Modelling for health and biology
Advanced numerical analysis
Statistics and Data Science Track:
Inferential statistics and linear models	Bayesian statistics
Modelling dependent data	Foundations of statistical learning
Data Science with R

Download syllabus

Examples of projects and internships

Examples of Past Projects

Portfolio optimization
Monte Carlo methods for rare event estimation
Patterns of Alan Turing
Portfolio risk measures
Population dynamics and breast cancer tumor growth modelling
Data mining for the analysis of petroglyphs
Numerical simulation of the transport of nuclear waste
Matrix completion for painting restoration
Multilevel Monte Carlo methods for option pricing
Study of the graph of Erdos Renyi
Numerical simulation of neural influx in neurons
Approximation power of deep neural networks
Introduction to quantum computing

Examples of past internships

Classification and Forecasting of load curves (GDF Suez strategy division)
Outsourcing of post-trade tasks (Accenture)
Integration of external variables to optimize hotel prices (Amadeus)
Development of a simulator (Thalès Alenia Space)
Reporting of investment funds (Prévoir)
Environmental characterization of the aircraft fleet (Safran)
Actuarial problems in reinsurance (Wills Re)
Reliability assessment of hybrid dynamical systems (EDF, Division Management of Industrial Risks)
Reporting of market risks for gas portfolio (EDF, Division Economy, Rate and Price)
Combination of statistical models for photovoltaic power forecasting (Reuniwatt)
Optimization of a statistical tool for sale forecasting (PSA)
Stochastic methods for the solution of high-dimensional PDEs (Centrale Nantes)
Passenger traffic forecasting models for decision supprt (SNCF)
Machine Learning applied to market abuse (HSBC)
NLP for automatic processing of legal documents (Stackadoc)
Optimization for precision viticulture (INRA)
Prediction of annuity revaluation costs (Generali)
Peptide retention time prediction (Functional Genomics Center Zurich)

After the specialisation