- Degree
- Master of Science in Electronics Engineering
- Course location
- Bremen
- Teaching language
- • English
- Languages
- Courses are held in English (100%).
- Full-time / part-time
- • full-time
- Programme duration
- 3 semesters, 4 semesters
- Beginning
- Winter and summer semester
- Additional information on beginning, duration and mode of study
- All courses are taught in person and include intense practical lab work. Lectures are supported by blended learning methods.
Find more info: https://www.hs-bremen.de/en/study/degree-programme/electronics-engineering-msc/ (https://www.hs-bremen.de/en/study/degree-programme/electronics-engineering-msc/)
- Application deadline
- Three-semester course of study for applicants holding a Bachelor's equivalent to 210 ECTS credits:
• winter semester: 1 June to 15 July
• summer semester: 15 December to 15 January
Four-semester course of study for applicants holding a Bachelor's equivalent to 180 ECTS credits
• only summer semester: 1 June to 15 October
via https://campino.hs-bremen.de/qisserver/pages/cs/sys/portal/hisinoneStartPage.faces (https://campino.hs-bremen.de/qisserver/pages/cs/sys/portal/hisinoneStartPage.faces)
- Tuition fees per semester in EUR
- None
- Combined Master's degree / PhD programme
- No
- Joint degree / double degree programme
- No
- Description/content
- We offer two profiles indicating the professional orientation in the field of Intelligent Systems:
• Development and fabrication of intelligent systems
• Application of intelligent systems
Depending on the collections of course modules attended, this qualifies students for professional careers in the following fields:
• Machine learning, artificial intelligence and signal processing in sensorics
• Autonomous vehicles
• Automated test and measurement, IIOT, intelligent sensors, edge control
• Microelectronics and microsystems design and fabrication
• System-on-Chip design, mixed-signal electronics
• Optical technologies and LASER systems
• Satellite-, wireless-, underwater- and fibre optic communication systems
• Aerospace application
Content
• design of integrated circuits and systems
• FPGA programming
• mixed signal systems design
• fundamentals of machine learning
• hardware implementation of AI
• microstructuring of silicon
• laser microprocessing
• microsensors and microactuators
• medical, environmental and automotive applications of microsystems
• automated measurement and test
• machine learning and pattern recognition
• signal processing in measurement and instrumentation
• technical optics, optical sensors, laser measurement
• electrical measurement of non-electric quantities
• satellite and wireless communications
• optical communications
• digital signal processing
• microwave engineering
• underwater acoustics and SONAR