Photonic computers for quantum and classical information processing

Are you excited about experimentally exploring the crossover from photonic computing to photonic quantum computing in the context of space technology?

We plan to open a position (up to 100 % TV-L E13) at the Chair of
Space Technology at TU Berlin in collaboration with the Physical Foundations of IT Security
Fundamentals of IT Security from January 2025 to December 2026.

Job description:
The research interest of our team is focused on fundamental methods and technologies as
well as applications of optical systems for classical and quantum information processing.
On the methodological side, this primarily includes quantum light sources and photonic
quantum memories for storing non-classical states of light. On the application side, this
concerns repeater-based quantum communication, photonic quantum computers and optical
neuromorphic computing architectures for machine learning.
Together with several PhD and MA students and industrial partners, you will work in our
project team to drive forward the development and testing of a photonic computer
architecture (see figure). These will then be used to demonstrate photonic computing
functions with applications in the field of machine learning and quantum information
processing for space-relevant tasks.
Your research will lay the foundation for energy-efficient photonic computers in the classical
and quantum quantum domain, which will also be able to work under the demanding
conditions on satellites in the future. Such computers have a high potential to enable energy-
efficient high-performance computing in orbit and would thus lead to a technological leap in
space technology.

Our requirements:
- Master's degree in physics or a closely related subject is required
- Demonstrated thorough knowledge and expertise in experimental optics, quantum
optics and/or photonic computing
- Experience in the development and implementation of optical laboratory experiments
- First experience in programming lab setups or neural networks with Python
- Good knowledge of the English language
- Experience in project management is an advantage

For further information about the call for applications, please contact Prof. Dr Janik
Wolters, j.wolters@tu-berlin.de, Tel. +49 3067055-7906.