GREEN Graduate Program - Mathematics, Modeling and Applications to Energy and Environment (M2A2E)
Pau, France
DURATION
2 Years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
31 Mar 2025
EARLIEST START DATE
Sep 2025
TUITION FEES
EUR 3,879 / per year
STUDY FORMAT
On-Campus
Introduction
The Mathematics, Modeling, and Applications to Energy and Environnement research graduate program aims to form experts with up-to-date knowledge of advanced skills in Applied Mathematics, Statistical and Machine Learning Methods, and Scientific Computing to elaborate, analyze, and simulate mathematical models arising from issues and predicted impacts in energy and environment.
Several key challenges are addressed in this program, such as:
- Elaboration of complex and accurate mathematical models arising in energy and environment,
- Optimization, combination, and implementation of advanced simulation methods associated with computer tools.
This degree offers multidisciplinary key courses to achieve an advanced specialist level in all areas involving mathematical modelling (deterministic and stochastic) and numerical simulation. It is suited for students planning both an academic or an industrial career and provides the theoretical basis and the practical expertise required to pursue academic research or R&D structures.
Admissions
Curriculum
Interdisciplinarity and research immersion in laboratories
To promote transversal and interdisciplinary activities, all the Graduate Programs proposed by GREEN are identically structured. In addition to the research training which represents 40% of a Master’s credits, the courses offered in each program are a combination of standard thematic culture courses in the field of Energy and Environment (Sustainability Science, Resilience Alliance, Ecological Economics, and Political Ecology, Health & Ecotoxicology, Energy Law & Policy…) and essential soft skills completed by fundamental and specialized disciplinary courses to fit with the research or topic interest of the students.
Training by project
The research-based training program of our GREEN project follows the active educational approach of “student-based learning”. The aim is to guide our students and help them structure their research and innovation projects while giving them a great deal of autonomy.
In the second year, there is therefore a significant reduction in the number of face-to-face courses in favor of project-based learning, to put students in a professional situation so that they can experiment with group work and project management. This framework encourages strong interaction between students, lecturers, and researchers to ensure easier integration into the host research laboratories. The interdisciplinary project proposed in the third semester should give students from all the graduate programs an opportunity to produce joint, multidisciplinary work.
Semester 1 Electives (ECTS 16)
- Numerical Analysis of Partial Differential Equations (PDEs) – 4 ECTS
- Optimization – 4 ECTS
- Scientific Computation with Python – 4 ECTS
- Statistical Inference – 4 ECTS
- Probability Calculus – 4 ECTS
- Hilbert Space – 4 ECTS
- Analysis of PDE – 4 ECTS
Semester 2 Electives (ECTS 10)
- Electives 1 – 6 ECTS
- Advanced Analysis – 6 ECTS
- Linear Model – 6 ECTS
- Markov Chains – 6 ECTS
- Electives 2 – 4 ECTS
- Scientific Computing – 4 ECTS
- Monte Carlo Methods – 4 ECTS
- Advanced Analysis of PDEs – 4 ECTS
Semester 3 Electives (ECTS 6)
- Mathematical Engineering for Machine Learning – 6 ECTS
- Advanced Numerical Analysis – 6 ECTS
- Advanced Analysis of PDEs 2 – 6 ECTS
Program Outcome
Objectives
- To contribute to the development and use of renewable energies and sustainable development, through fine mathematical and numerical modeling of the physical phenomena involved at different scales.
- To train top-level students for careers in academic or private research in applied mathematics in the scope of major energy and environmental challenges.
- To train students to develop cutting-edge mathematical and computational skills to deal with complex problems in industry and design offices.
Skills
At the end of the training, the students will be able to :
- Carry out initial research in applied mathematics at LMAP, in line with major energy and environmental issues and challenges.
- Solve problems to develop new knowledge and procedures, and integrate knowledge from different fields.
- Make innovative contributions in the context of high-profile exchanges, and international contexts in connection with energy and environmental issues.
- Conduct a reflective and distanced analysis, taking into account the stakes, issues, and complexity of the problem under study.
- Understand and analyze energy and environmental problems from the point of view of numerical modeling.
In particular, he/she will be able to demonstrate advanced interdisciplinary skills:
- Deterministic or stochastic modeling of the problems under consideration
- Numerical simulation and computer implementation of established models
- Optimization of underlying algorithms to deal more effectively with problems involving large and/or complex data sets
- Statistical processing of large and complex data flows for decision support and reliability.
Career Opportunities
Sector
- Industry
- Academic
Fields
- Research
- R&D structures
Positions
- Academic positions
- Researchers (public institutes or private companies)
- Research and Innovation Engineers