Master thesis Modeling and Intelligent Control of a Dual-Input RF Power Amplifier System – 0726

The Ferdinand-Braun-Institut Leibniz-Institut für Höchstfrequenztechnik (FBH) is an application-oriented research institute in the fields of high-frequency electronics photonics and quantum physics. It researches and realizes electronic and optical components modules and systems based on compound semiconductors. These devices are key enablers that address the needs of todays society in fields like communication energy health and mobility.

The focus in the RF Power Lab is on applications with output powers in the range of 5...200 W in the microwave range up to 40 GHz. We work on novel concepts to increase efficiency in broadband modulated power amplifier systems for modern telecommunication and signals with high peak-to-average power particular we investigate dual-input amplifier systems based on load & supply-voltage modulation and how to use them in AI-controlled intelligent self-tunable systems. Integrated reconfigurable components and circuits are also in focus and more advanced integrated transceivers for radar and addition we develop novel autonomous RF measurement systems for improved RF power transistor characterization and the optimization of such devices based on machine learning.

Reference number 07/26

Your tasks (with focus depending on backround)

of a novel behavioral model for a supply voltage modulated dual input dual output (DIDO) system over large temperature variation

• Acquiring experimental data for the ET PA at different temperatures T1 T2
• Identify model parameter for a recently developed DIDO model for each temperature
• Use machine learning (ML) to create a model for the parameter dependence
• Verify the model for experimental data
  

2.Control and optimization of PA performance for temperature variations

• Develop a ML model for control of the DIDO
• Train the ML model based on the behavioral model in task 1
• Verify the ML model based on experimental data

Your profile

• On-going master studies in Computer Science. Electrical Engineering Communications and Signal Processing or Physics with Applied Mathematics
• Knowledge of machine learning signal processing microwave engineering nonlinear and behavioral modeling AI-based modeling
• Interest in applied mathematics signal processing
• Experience in Matlab and Python (preferably)
• Starting date: a.s.a.p.

Our offer

• an open and appreciative international team always available with help and advice
• a modern workplace in Berlin Adlershof with good public transport connections
• exciting insights into practical applications and the opportunity to gain valuable experience
  

Does it sound interesting Then we look forward to receiving your online application. To apply please click on Apply online and submit your complete application documents by April 13 2026.

If you have questions please contact Dr. Olof Bengtsson Tel.:-2643 E-Mail:

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