You can find current student projects at IDS here.

We are seeking for an excellent post-doc majored in microelectronics to drive our research in the domain of neuromorphic computing. Taking a digital perspective your scientific work will stretch from modern-day algorithms to the capabilities of modern manufacturing technologies incl. novel devices. You have demonstrated your skills in successful tape-outs during your PhD at a top-rated University. Also, you have an in-depth understanding of the digital / MS design flow from physical entry (transistor, layout) up to sign-off incl. the configuration of EDA tools. If you also bring in experience in fields such as Computing-in-Memory, DNN or low-power design, we would be excited to talk to you!


For more information:
Post-Doc Design digtial CIM

We would also like to make our contribution to interrupting the infection paths of the coronavirus.
Therefore, contacts are reduced to a minimum in our chair as well. This leads to the following restrictions.
We thank you for your understanding!

Availability of the Chair

We ask you to contact us primarily via email: This email address is being protected from spambots. You need JavaScript enabled to view it.
Personal appointments can then be arranged when necessary.

Lectures and Exercises

Due to the general regulations regarding lectures at the RWTH, lectures, tutorials and practical courses at IDS will also be held online only until further notice. Watch out for further information on this.


The CIP pool will remain closed until further notice.

Human Brain on Steroids 1

Since 2019, the chair of Integrated Digital Systems (IDS) participates in the “Advanced Computing Architectures” (ACA, Fig. 1) project that targets the accelerated simulation of biological neural networks. As much as science has discovered about the various electro-chemical processes in the brain, it remains still a secret of how it all adds up to create intelligence. To further advance the understanding, an essential step is the emulation of learning processes in the brain. As for a human it takes years, researchers need fast “turn-around times” to validate their assumptions in simulation. Furthermore, they would like to sweep parameters to find the best fit between the simulation results and data observed in nature.

Human Brain on Steroids 2Best-in-class HPC systems provide a simulation speed that more-or-less matches biological real-time. Within the ACA project, we target a 100x acceleration factor for biological networks of relevant complexity, i.e. covering about 10% of the human cortex down to detailed biological neuron models.

As a first step, we analyzed the challenge of communicating the spike information of the 109 neurons to its 104 ‘followers’ each. The work relies on various modelling efforts of the communication requirements and supportive hardware infrastructure [Kau20]. For benchmarking, it also requires a model of the biological communication network – the connectome (cf. Fig. 2 a sketch of such model). This simulation based exploration is supported with a physical cluster of FPGA boards (see Fig. 3 – provided by the Research Center Jülich) to emulate future system capabilities in order to calibrate the derived models.Human Brain on Steroids 3

Targeting the scientific community, it largely differs from the application oriented artificial neural networks as used for big data processing today. However, one day we foresee these efforts to converge providing artificial general intelligence to digital systems in our daily lives.





[Kau20] K. Kauth, T. Stadtmann, R. Brandhofer, V. Sobhani and T. Gemmeke, “Communication Architecture Enabling 100x Accelerated Simulation of Biological Neural Networks”, Proc. ACM/IEEE Int. Workshop on System-Level Interconnect Problems and Pathfinding (SLIPˆ2), 2020. doi: 10.1145/3414622.3431909