Technische Universität Darmstadt
5 days ago
Research Associate / PhD Candidate in Telecommunications Systems, Model-Based Deep Learning for 6G Networks Technical University of Darmstadt in Germany
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
Sep 2, 2026
Country
Germany
University
Technische Universität Darmstadt

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About this position
Research Associate / PhD Candidate (m/f/d) in Telecommunications Systems at Technical University of Darmstadt (TU Darmstadt), Germany.
The position is in the area of Communication Systems within the Department of Electrical and Information Engineering, with research focused on statistical signal processing, mathematical optimization, machine learning, and especially model-based deep learning for robust 6G networks.
Research topics include model-based learning methods for parameter estimation, signal detection, and resource allocation in mobile networks, with implementation in PyTorch. The role also involves publishing results in leading international journals and conferences.
This is a PhD-opening research associate role with a 3-year temporary contract, 100% employment, and remuneration at pay group 13 TV TU Darmstadt. The university states that the position serves as scientific qualification and offers the opportunity to prepare a doctorate.
Requirements include a very good completed M.Sc. or equivalent in electrical engineering, information technology, or a related field; strong knowledge of signal processing, optimization, and deep learning; practical Python and PyTorch skills; and interest in scientific publishing. English proficiency is required, and German is an advantage.
Supervisor/contact: Prof. Dr.-Ing. Marius Pesavento ([email protected]).
Deadline: 2026-09-02. Apply online through the TU Darmstadt job portal.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
More information can be found here
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