Research Associate
vor 3 Wochen
TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most
dynamic research institutions in the country. Founded in 1828, today it is a globally oriented,
regionally anchored top university as it focuses on the grand challenges of the 21st century. It
develops innovative solutions for the world's most pressing issues. In research and academic
programs, the university unites the natural and engineering sciences with the humanities, social
sciences and medicine. This wide range of disciplines is a special feature, facilitating interdisciplinarity
and transfer of science to society. As a modern employer, it offers attractive working conditions to all
employees in teaching, research, technology and administration. The goal is to promote and develop
their individual abilities while empowering everyone to reach their full potential. TUD embodies a
university culture that is characterized by cosmopolitanism, mutual appreciation, thriving innovation
and active participation. For TUD diversity is an essential feature and a quality criterion of an excellent
university. Accordingly, we welcome all applicants who would like to commit themselves, their
achievements and productivity to the success of the whole institution.
At the** Faculty of Electrical and Computer Engineering, Institute of Circuits and Systems,** the
offers a position as
**Research Associate / PhD Student / Postdoc **(M/F/x)
**Diffractive Neural Networks for Fiber-optical Information Processing**
starting **as soon as possible.** The position is limited to 30 months. The period of employment is
governed by the Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz - WissZeitVG).
The position offers the chance to obtain further academic qualification (usually PhD / habilitation).
Fiber-optical networks are the backbone of the global internet infrastructure. However, multimode
fibers provide additional channels for data transmission by multiplane light conversion. The goal is to
exploit novel optical diffractive neural networks for high fidelity space division multiplexing. The
optical neural networks operate with high speed, low latency, and low energy consumption (non von
- Neumann architecture).
**Tasks**: Innovative concepts for light control in multimode fibers are investigated towards
(de)multiplexing of optical states via the spatial degrees of freedom. High-dimensional quantum
states (qudits) will be included. Your activities include the realization of multimode fiber systems with
diffractive neural networks, the characterization of the light transmission properties and the transfer
science, physics or related areas; ability and willingness to work independently and conceptually in a
dynamic team; curiosity in research at interfaces of sciences Interest in practice-oriented,
interdisciplinary cooperation with partners from research and industry; knowledge of software
development and digital signal processing. Previous knowledge of AI/ML/DNN, technical optics,
quantum optics, MATLAB or Python is advantageous.
**We offer**: Living and success in Florence at the Elbe; Laboratories with modern equipment, excellent
contacts in research and industry, visiting international conferences and an interdisciplinary, flexible
team.
TUD strives to employ more women in academia and research. We therefore expressly encourage
women to apply. The University is a certified family-friendly university and offers a Dual Career
equally qualified, those with disabilities or with equivalent status pursuant to the German Social Code
IX (SGB IX) will receive priority for employment.
**TU Dresden, Fakultät Elektrotechnik und Informationstechnik, Institut für Grundlagen der**
**Elektrotechnik und Elektronik, Professur für Mess
- und Sensorsystemtechnik, Herrn Prof. Dr.**
**Ing. habil. J. Czarske, Helmholtzstr. 10, 01069 Dresden, Germany** or as a single pdf file to** grp-mst-**
you. Expenses incurred in attending interviews cannot be reimbursed.**
**Reference to data protection**: Your data protection rights, the purpose for which your data will be processed,
- dresden.de/karriere/datenschutzhinweis.
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