Bachelor Computational Sciences

The Bachelor in Computational Sciences (BaSC) constitutes the first part of a basic education. It aims to provide a multidisciplinary education that will enable students to meet future scientific and societal challenges related to the expansion of computer science with other disciplines in the natural and social sciences. This course is based on two fundamental foundations. The first is learning the methodological tools essential to the mastery and use of computer sciences: mathematics, scientific programming, modeling, analysis and representation of massive data. The second is based on the knowledge and in-depth understanding of an application domain in which computer science plays an essential role. The specific study plans for each application area are as follows


  • Bachelor in Computational Sciences orientation Biology (BaSC-Bio): Biology and Computer Science offer a joint curriculum focused on the emerging field of computational biology that involves the development and application of data analysis methods, theoretical approaches, mathematical modeling, and digital simulation techniques to study complex biological systems. The interdisciplinary curriculum provides a strong foundation in applied mathematics, statistics, physics, molecular biology, genetics, genomics, evolution, and computer science/programming to enable future graduates to address research and development challenges and opportunities at the interface between computer science and the life sciences. This new program responds to the growing needs in this multidisciplinary field in academic research and industry (pharmaceutical field, software development, bio-inspired robotics, comparative genomics ...).
  • Bachelor in Computational Sciences orientation Earth and environmental sciences (BaSC-TerrEnv): Responding to current and future environmental and societal challenges requires the development and rapid implementation of novel approaches for sustainable development and adaptation of our societies to global changes. In this context, the modern geosciences expert is able to mobilize a variety of scientific and technical cross-disciplinary skills in order to make the best use of the constant flow of new Earth and environmental observation data, and the increasingly sophisticated computer tools that allow their analysis. The BaSC-TerrEnv orientation prepares the future actors of a sustainable future capable of using all the modern tools in the service of understanding and conserving the environment.


Course methodology / 90 ECTS credits

  • Mathematics, numerical analysis, probability and statistics
  • Scientific programming (algorithms, Python, C++, parallelism, GPU)
  • Data science (data structures, information theory, data mining, AI, data representation)
  • Modeling (complex systems, natural phenomena)

One field of application to choose from / 90 ECTS credits

  • Biology : Basic biology, genetics, animal physiology, biochemistry, general physics, animal and plant development, bioinformatics, evolution, molecular biology, etc.
  • Earth and Environmental Sciences: Structural geology, geophysics, geo-data, geomatics, volcanology, environmental chemistry and biochemistry, ecology, etc.

Academic opportunities

Obtaining a Bachelor's degree in Computational Sciences allows access to the second course of study of the basic education, i.e. the studies for a Master's degree in Computer Science or in the field of the chosen orientation and subject to the admission requirements specific to the Master's degree applied for.

  • The orientation in biology allows access to the following courses:
    • Master's degree in biology with a free or targeted orientation
    • Interfaculty Master's degree in neuroscience (upon application)
    • Master in chemical biology (upon application)
    • Master's degree in biomedical sciences (upon application)
  • The orientation in Earth and Environmental Sciences allows access to the following courses:
    • Master in Environmental Sciences (MUSE)
    • Master's degree in Earth Sciences (joint in the framework of ELSTE)