General information
- Duration : 2 years
- Place : Nantes
- Language : English and French
The Graduate Programme Smart Computing (GP SMART) trains high-level engineers and researchers capable of working at the forefront of digital technology and pushing its boundaries. The GP Smart Computing programme awards two degrees:
Students can integrate the GP smart computing in Master 1, Master 2 and D1. The GP SMART programme is one of the six programmes of the Master in Computer Science of Nantes-Université : GP Smart Computing, ALMA: Software engineering, ATAL: Natural Language Processing, ORO : Operational research, DS: Data Science, VICO: Visualisation. It is possible for students to switch to another programme of the Master at the end of M1. Compared to other programmes of the Master, the GP Smart Computing is research oriented and better prepared for the Ph.D.
Smart computing is a multi-disciplinary area where advanced computational methods and technologies are combined with engineering approaches to create systems, applications and new services that meet the needs of society. Whatever we think about in real society, there are now its digital twins allowing better efficiency, personalisation, safety and sustainability. For example, Smart cities should enhance the quality of life for its residents while promoting sustainability, efficiency, and economic growth. Smart grids enhance the efficiency, reliability, and sustainability of electrical power distribution and consumption.
Working on the smart evolution of society requires not only high-level engineering skills but also new knowledge. The ability to build new knowledge and use it to address new society needs is the heart of the GP Smart Computing.
The student will be integrated into the LS2N research laboratory. The LS2N is the largest public research unit in Nantes and the Pays de la Loire region.
The LS2N has a staff of over 480 people, half of whom are permanent, distributed across 5 sites: Faculty of Science and Technology, Centrale Nantes, Polytech Nantes, IMT Atlantique, and IUT Nantes. Research at LS2N is conducted within 24 research teams, structured around 5 major scientific areas: Signals, Images, Ergonomics, and Languages; Data Science and Decision Making; Software Science and Distributed Systems; System Design and Operation and Robotics, Processes, and Computation. In addition to these 5 areas, there are 6 cross-cutting application themes: Future Enterprises, Energy Management and Environmental Impact Control, Life Sciences, Vehicles and Mobility, Creation, Digital Culture, and Society, and Digital Technology for Open Education.
The LS2N is connected to the local socio-economic sphere, to other research laboratories for conducting multidisciplinary research.
The objective of the research immersion is to let students progressively discover key topics and key people they like, define a research project in a domain area and start producing knowledge in that domain. The mentor researcher helps students to understand and navigate among the LS2N opportunities.
Students can join the Programme either at the Master’s level or at the PhD’s level. After the first two years, students who have obtained the master’s degree can apply for PhD or pursue other career paths as research and innovation engineer.
Figure 1
A smart computer engineer combines expertise in digital engineering and research. To acquire both expertises, the student follow the following program:
The GP SC targets engineering and research skills.
The Master in CS award delivers skills defined at the national level for a master in computer science along with a part of skills defined for research as defined in figure 2.
The expected skills for a master in computer science are:
These skills are acquired thanks to participation in the core courses of the GP master (50% of ECTS). Research learning also contributes actively to these skills in the professional context of research.
The expected skills in research are:
Supervision of teams dedicated to research and development, study, and foresight activities
The learning situations of the GP Smart computing at the master level target skills 1, 2 and 4. The other skills are planned for the Ph.D level.