Applied mathematics


The Master in Mathematical Engineering is an interdisciplinary engineering master centred on the notion of mathematical model that has become instrumental in engineering sciences. Through a training in modelling, simulation and optimization (MSO), the students learn to design, analyse and implement mathematical models and algorithms, and to apply them to complex systems of the industrial or corporate world in order to simulate and control their behaviour, predict their evolution, and optimize their performance.

The mandatory courses provide the students with the necessary common skills in MSO. They span the domains of numerical analysis and scientific computing, dynamical systems, matrix computations, stochastic models, optimization models and methods. Students are moreover offered several coherent lists of courses, called "options". Some of the options provide them with advanced skills in various branches of MSO: optimization and operations research, dynamical systems and control, and computational engineering. The other options pertain to data science, financial mathematics, cryptography & information security, biomedical engineering, business risks and opportunities, and launching of small and medium-sized companies. UCL is the only French-speaking university in Belgium to offer a master in Mathematical Engineering. Dual Master agreements exist with KU Leuven's Master of Mathematical Engineering and with KTH Stockholm's Master in Applied and Computational Mathematics. These agreements make it possible to obtain both UCL's and the host university's master diploma at the end of a two-year master programme.

The Master in Mathematical Engineering provides a versatile multidisciplinary education that is highly valued by high tech companies. It opens up a number of job prospects in production and service companies, IT businesses, banks, and the public sector. Our engineers are currently employed, inter alia, in consulting, energy, finance, insurance, aerospace, telecommunication, transportation and pharmaceutical companies. They work on applications such as optimal planning of networks for communication, distribution and transportation; real-time control of industrial processes (chemistry, biotechnology, etc.); automatic control of complex electromechanical systems (robotics, aerospace, etc.); prediction of economical or environmental variables; numerical simulation of complex systems (biomedical engineering, fluid mechanics, climatology, etc.).