Master in Electrical Engineering Science

Year 1: Electrical Engineering for Communications & Information Processing

This first year of the Master’s program in Electrical Engineering for Communications provides students with courses in the basic sciences in English, as well as a French language course. Students can choose from four majors that will set the path for their specialization in the second year.

The first major is Telecommunication Networking and Multimedia. It aims to provide the foundations to understand, practice, and contribute to the development of new-generation communication techniques and networking, content-coding, and delivery systems such as 5G networks, connected devices, machine-to-machine communication, as well as the need for very low-delay and high-reliability networks.

The second major is DATA Analysis and Pattern Classification. It provides the tools to process all types of real data captured by sensors. Reinforced and extended in the second year, this program enables students to model real and noisy data, retrieve information from very large databases, and design complex systems based on these techniques. It has many applications including telecommunications, medical imaging, virtual reality, telemonitoring, biometrics, bioinformatics, environmental sciences, banking, insurance, and data mining.

The major in Electrical and Optical Engineering allows students to develop original thinking and the ability to anticipate. The program is based on multidisciplinary application fields in both electronics and optics. It encompasses core training addressing fundamental aspects, as well as focusing on specific technical skills in different applications such as communications, sensors, defense and space, automotive, and information technology.

The major in Microelectronics addresses CMOS integrated technologies and the emergence of the micro/nanotechnologies, as well as the complexity of today’s integrated systems. The program covers new technological possibilities including the implementation of high-performance, high-value, multi-domain integrated systems. It provides students with training to address system performance optimization based on specifications obtained by co-designing the different parts. This requires a good knowledge of all the devices used in the system.

Focus on Year 2 specialization: Machine Learning, Communications and Security

The second year of the Machine Learning, Communications, and Security Master’s program is devoted to information sciences and explores solutions to efficiently process, transmit, store, and protect information. This cross-disciplinary program starts with foundational courses in information processing, building around three main areas: machine learning, communications theory and technologies; and security.

This research-oriented program provides students with strong academic training in data processing and an in-depth knowledge of communication technologies, machine learning algorithms and information security methods. The first semester encompasses courses taught by faculty members from three Institut Polytechnique de Paris laboratories. During the second semester, students will complete an internship for a minimum four-month period.

This second-year Master’s program offers mathematically-minded students a strong background in the fundamentals of information processing and related technologies, preparing them to pursue a career in academia or industry.

Year 2: Other specializations

• Embedded Systems and Information Processing
• Information Processing and Data Exploitation
• Multimedia Networking
• Optical Networks and Photonic Systems
• Radio Systems
• Virtual and Augmented Reality

Career

Students graduating from this program will be able to:

• Pursue a research or development career in a higher education institution or industry in a wide range of fields including Information and Communication Technologies (ICT), biology, healthcare, energy, transportation, and manufacturing
• Pursue a PhD enabling them to then occupy positions such as researchers and project managers in R&D companies or research fellows and professors in academic institutions