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Research Fellow/PhD Student (f/m/d)
Intelligent Architectures for Future Machine Learning

Organizational unit

Institute for Computer Engineering (ITEC)

Job description

In the Department of computer science at the Institute of Computer Engineering, Chair for Embedded Systems (CES), we focus our research on neural network, computer architecture, and emerging technologies. As a matter of fact, computing systems have reached a point, where significant improvements in computational performance and efficiency have become profoundly hard to achieve. When it comes to Deep Neural Networks (DNNs), existing architectures are severely bottlenecked by the massive amount of data that must be transferred, which goes far beyond the communication capability of our modern systems.

In this project, we will investigate how recent breakthroughs in architectures, in which novel concepts of near-memory and in-memory computing are employed, leads to more efficient and higher performance training and inference of deep neural networks. We will also explore how innovations in the underlying technologies, in which advanced Non-Volatile Memory (NVM) devices, are in use open doors for more intelligent machine learning in the future.

Starting date

as soon as possible

Personal qualification

The following qualifications are required seeking your consideration for this position.

  • MSc degree (or equivalent) in Electrical Engineer or Computer Science.
  • Good English skills.

Skills in one or more of the following areas is recommended

  • Hardware accelerators for neural networks.
  • Computer architecture
  • FPGA-based Designs.
  • Programming skills in C/C++, or scripting languages like Python


Salary category 13, depending on the fulfillment of professional and personal requirements.

Contract duration

limited to 3 years and can be extended for two more years

Application up to


Contact person in line-management

For further information, please contact Dr. Hussam Amrouch,, Tel: +49(0)721/608-45733.

Please apply online using the button below for this vacancy number 1023.

Ausschreibungsnummer: 1023

If qualified, severely disabled persons will be preferred.


Personnel Support is provided by:
Ms Brückner
Phone: +49 721 608-42016,

Kaiserstr. 12, 76131 Karlsruhe