Faculty of Electrical and Computer Engineering
At the Institute of Communications Engineering, the Deutsche Telekom Chair of Communication Networks offers two project positions under the BMBF project DAKORE as
Research Associate (m/f/x)
(subject to personal qualification employees are remunerated according to salary group E 13 TV-L)
starting as soon as possible. The positions are limited until June 30, 2025. The period of employment is governed by § 2 (2) Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz – WissZeitVG).
The purpose of this project is to reduce the energy consumption of future radio access networks by developing advanced power amplifiers and network management through artificial intelligence/machine learning algorithms. In this context, ComNets leads the efforts in network-level optimization. The project will be carried out in cooperation with other chairs at TUD and industrial partners.
Task: The successful candidates will be working on implementing a simulation model of a radio network and on radio resource allocation using machine learning algorithms in the context of the project DAKORE, funded by the German Federal Ministry of Education and Research. Under the assumption of advanced power amplifiers, that provide high energy efficiency for a range of operating points (the power amplifiers will be developed by another chair at TUD), a distributed artificial intelligence can adaptively control the network to reduce the energy consumption while maintaining a high quality of service for all users. This includes the adaption of parameters of a set of access points (e.g., transmission power) and the allocation of users to these access points (different access points may use different frequency ranges). The envisioned dynamic control of a distributed network can, for example, be tackled using multi-agent reinforcement learning. In order to ensure seamless compliance with the requested quality of service of all users, a predictive engine may also be part of the overall system. The project leaves much space for creativity and the implementation of the candidates’ interests. Successful candidates will be required to perform the following tasks:
- Carry out research in the emerging topic artificial intelligence for radio resource allocation (both developing a network simulation and an intelligent network management system).
- Collaborate with colleagues at TUD and with industry partners.
- Disseminate results through scientific publications in the top-tier venues.
- Present results in top-tier international conferences and workshops.
- The position may also include minor teaching duties and/or contributions in the development of new research proposals.
- The candidate should possess a university degree in electrical engineering, telecommunication engineering, computer science, or equivalent.
- The ideal candidate should have knowledge and experience in several of the following topics:
- wireless communications, in particular in the context of 5G,
- wireless network simulation,
- machine learning, in particular multi-agent reinforcement learning,
- radio resource allocation/ Radio resource management (e.g., bandwidth and power allocation, scheduling, etc.).
- An understanding of power amplifiers and high-frequency hardware is beneficial towards understanding the larger picture of the project but not required.
- Good programming skills are required. Highly relevant programming languages are Python, C++, and MATLAB.
- Fluent written and verbal communication skills in English are required.
Applications from women are particularly welcome. The same applies to people with disabilities.
Please submit your application documents until August 17, 2022 (stamped arrival date of the university central mail service applies) preferably via the TU Dresden SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf document to email@example.com or to: TU Dresden, Fakultät Elektrotechnik und Informationstechnik, Institut für Nachrichtentechnik, Deutsche Telekom Professur für Kommunikationsnetze, z. Hd. Frau Karin Domel, Helmholtzstr. 10, 01069 Dresden. Please submit copies only, as your application will not be returned to 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, as well as further information about data protection is available to you on the website: https://tu-dresden.de/karriere/datenschutzhinweis.