Internet of things
This Bordeaux Summer School is designed for graduate and doctoral students from the fields of electrical engineering, computer science, data science and applied mathematics, and who have an interest in the topic of the Internet of Things and its environmental and societal impacts.
Throughout the program, renowned and dynamic speakers will share their insight on the latest advances and applications of the Internet of Things technology as a driver for innovative digital infrastructures. Course content covers a wide scope of themes, including:
- Radio communications
- Communication techniques
- Data processing
- Machine learning
- Deep learning
Hands-on tutored workshops complement the theoretical sessions, enabling participants to design, create and program a connected object of their choice. Seminars on applications in e-health, energy harvesting, intelligent transport systems, etc. will conclude each day.
19 Sep 2022 - 23 Sep 2022
Master / Graduate
|Program fee||600 EUR|
|Accommodation fee||Included in program fee|
|Extra information about the
› 50€ for students from the University of Bordeaux (including lunches, coffee breaks and social program costs)
› 400€ for students from partner institutions* (including lunches, coffee breaks, accommodation and social program costs)
› 600€ for other participants (including lunches, coffee breaks, accommodation and social program costs)
*Partner institutions: members of the ENLIGHT consortium, ESTIA Institute of Technology, Basque Center for Applied Mathematics, Limoges University.
|Application deadline||5 June 2022|
The course is designed for graduate and doctoral students in the fields of electrical engineering, computer science, data science and applied mathematics.
Language requirements: classes and exchanges are conducted in English. Candidates should have at least a B2 level of English or equivalent.
Candidates must provide a CV and cover letter detailing their scientific interest for attending the summer school. Graduate students must provide the coordinates of a referring teacher. Doctoral students must provide the name of their advisor and subject of their PhD thesis.