Teaching

Courses

The Institute of Neuromorphic Computing offers courses on memory technologies, mixed-signal circuits, field theory and neuromorphic computing and contributes to courses of other institutes of the faculty. The courses are assigned to the Master's programmes in Electrical Engineering, Industrial Engineering/Electrical Engineering, Computer Science, Electromobility and Quantum Technologies as well as to the Master Microelectronics Engineering. Contents, learning outcomes, literature and current dates are given on the individual course pages, registration and materials are available in Stud.IP.

Winter semester

• Emerging Memory Technologies, lecture and exercises, English: phase-change, resistive, magnetic and ferroelectric memories compared with Flash, DRAM and SRAM
• Analog-to-Digital Converters, lecture and exercises, English: architectures, noise and design of A/D and D/A converters
• Technology Assessment, seminar, German, jointly with elenia, IMAB: effects of new technologies on society, environment and economy
• Electrical Fundamentals of Energy Engineering for Transport and Environmental Engineering, lecture and exercises, German, jointly with elenia, IMAB

Summer semester

• Neuromorphic Computing and Engineering, lecture and exercises, 5 credit points, English: principles of biological computation and their implementation in hardware
• Advanced Field Theory for QT and Microelectronics Engineering, lecture and exercises, English, compulsory course in the Master Microelectronics Engineering
• Electronic Packaging and Interconnection Technology, lecture and exercises, German, jointly with Prof. Dr. Erwin Peiner (Institute of Semiconductor Technology)

Research seminar

• Group Seminar Neuromorphic Computing, online seminar by arrangement for students writing a thesis or project at the institute and for doctoral researchers

Theses, Projects and Lab Courses

Students can carry out Bachelor's and Master's theses as well as study and project work with us. Typical topics include the design of analog, mixed-signal and digital circuits for neuromorphic systems, the characterisation of ferroelectric devices, compute-in-memory architectures, and the training and compression of neural networks for hardware. Our lectures are complemented by hands-on experiments and CAD exercises.

Current topics and contact persons can be found on the Research and Team pages.