Master Thesis on Federated Learning for Internet of Things (IoT) Systems

Dlr; Oberpfaffenhofen; Remote; EUR 10,000 - 12,000; Part time

Job summary

DLR in Oberpfaffenhofen offers a Master Thesis on Federated Learning for IoT systems. The project focuses on NB-IoT MAC layer and uses the ns-3 simulator to study FL performance. You’ll optimize NB-IoT parameters for real-world IoT use-cases and contribute to state-of-the-art research.

The role requires strong C/C++ programming skills, a proactive, independent work approach, and good English. The position is part-time for six months starting 01.07.2026.

Qualifications

• Pursuing a Master’s degree in a relevant field and completing a final thesis.
• Experience with ns-3 simulations is desirable.
• Strong programming skills in C/C++.
• Knowledge of 3GPP NB-IoT MAC layer is beneficial.
• Good English skills.

Responsibilities

• Familiarize with 3GPP NB-IoT at the MAC layer.
• Familiarize with the ns-3 network simulator.
• Study FL over NB-IoT via ns-3 simulations.
• Optimize NB-IoT protocol parameters for practical FL use-cases.

Skills

MAC layer protocols

Federated learning

C/C++ programming

Event-driven simulations

Independent work

English language

Education

Master's student

Tools

ns-3 network simulator

Job description

Master Thesis on Federated Learning for Internet of Things (IoT) Systems Language Profile

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Master Thesis on Federated Learning for Internet of Things (IoT) Systems Job Description Req ID: 5055 Place of work: Oberpfaffenhofen Starting date: 01.07.2026 Career level: Student research project and final thesis, Student employment Type of employment: Part time Duration of contract: 6 months

Remuneration:

Remuneration is in accordance with the Collective Agreement for the Public Sector - Federal Government (TVöD-Bund).

Enter the fascinating world of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e. V.; DLR) and help shape the future through research and innovation! We offer an exciting and inspiring working environment driven by the expertise and curiosity of our12,000employees from 100 nations and our unique infrastructure. Together, we develop sustainable technologies and thus contribute to finding solutions to global challenges. Would you like to join us in addressing this major future challenge?Then this is your place!

The DLR Institute of Communications and Navigation is dedicated to mission-oriented research in selected areas of communications and navigation. Its work ranges from the theoretical foundations to the demonstration of new procedures and systems in a real environment and is embedded in DLR's Space, Aeronautics, Transport, Security and Digitalization programmes.

What to expect

The Advanced Information Processing Group aims at applying state-of-the-art theoretical results into real-world applications within information processing systems. The expertise of the group ranges from quantum error correction to Smart Data Management, exploring cutting-edge communication theories such as semantic communication and Age of Information, pushing the boundaries of data utilization and dissemination.

The thesis will focus on the study and optimization, by means of network simulations, of federated learning (FL) solutions for Internet of Things (IoT) applications. Specifically, the possibility to efficiently support FL over 3GPP narrowband-IoT (NB-IoT), a core element of IoT connectivity in 4G, 5G and 6G systems, will be explored, with attention to MAC protocol aspects.

Your tasks

• Familiarize with the main aspects of 3GPP NB-IoT at the MAC layer
• Familiarize with the ns-3 network simulator
• Study, by means of ns-3 simulations how FL algorithms perform over NB-IoT
• Optimize the NB-IoT protocol parameters to efficiently support FL in use-cases of practical relevance

Your profile

• Good knowledge of communication systems and signal processing, with particular emphasis on MAC level protocols
• Interest in machine learning and federated learning
• Programming skills (C/C++) and willingness to learn new tools
• Previous experience with event-driven network simulations is a plus
• Ability to work independently and interest in interdisciplinary topics
• Good knowledge of English language

We offer

DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.

We look forward to getting to know you!

If you have any questions about this position (Vacancy-ID 5055) please contact:

Dr. Andrea Munari Tel.: [phone] - 28 3639